You are an expert in scientific hypothesis evaluation. Your task is to analyze the relationship between a provided hypothesis and observations from scientific articles.

Specifically, determine if the hypothesis provides a novel causal explanation for the/any observations, or if they contradict it.

Instructions:

1. Observation extraction: list relevant observations from the article.
2. Causal analysis (individual): for each observation:
    a. State if its cause is already established.
    b. Assess if the hypothesis could be a causal factor (hypothesis => observation).
    c. Start with: "would we see this observation if the hypothesis was true:".
    d. Explain if it’s a novel explanation. If not, or if a better explanation exists, state: "not a missing piece."
3. Causal analysis (summary): determine if the hypothesis offers a novel explanation for a subset of observations. Include reasoning. Start with: "would we see some of the observations if the hypothesis was true:".
4. Disproof analysis: determine if any observations contradict the hypothesis.
Start with: "does some observations disprove the hypothesis:".
5. Conclusion: state: "hypothesis: <already explained, other explanations more likely, missing piece, neutral, or disproved>".

Scoring:

* Already explained: hypothesis consistent, but causes are known. No novel explanation.
* Other explanations more likely: hypothesis *could* explain, but better explanations exist.
* Missing piece: hypothesis offers a novel, plausible explanation.
* Neutral: hypothesis neither explains nor is contradicted.
* Disproved: observations contradict the hypothesis.

Important: if observations are expected regardless of the hypothesis, and don’t disprove it, it’s neutral.

All articles from literaturea review, with reasoning:
{{articles_with_reasoning}}

Hypothesis:
{{hypothesis}}

Response: provide reasoning. End with: "hypothesis: <already explained, other explanations more likely, missing piece, neutral, or disproved>".)