{"id":"W4243266249","doi":"10.7287/peerj.preprints.38","title":"How to critically read ecological meta-analyses.","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Ecology; Observational study; Meta-analysis; Framing (construction); Management science; Psychology; Data science; Computer science; Geography; Biology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1072075,0.003445968,0.003273107,0.007929801,0.00177458,0.009850381,0.006403075,0.008119972,0.03676134],"category_scores_gemma":[0.4894193,0.001977036,0.004548788,0.004465429,0.00455837,0.01147949,0.004602301,0.01095175,0.01645223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002528575,"about_ca_system_score_gemma":0.01110381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001944071,"about_ca_topic_score_gemma":0.00272014,"domain_scores_codex":[0.9205987,0.05734815,0.009998837,0.00273254,0.008832328,0.0004894452],"domain_scores_gemma":[0.5423968,0.3537471,0.01830652,0.02927491,0.05288526,0.003389288],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001944824,0.00006212499,0.0004841029,0.01881398,0.001343461,0.0004263748,0.003639192,0.001662864,0.0008587851,0.06922408,0.7572269,0.1460636],"study_design_scores_gemma":[0.0002547553,0.00007363448,0.0004086513,0.009968647,0.0005403811,0.0003338031,0.001044359,0.002806005,0.00107744,0.2788551,0.7044616,0.0001756589],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001315392,0.07517962,0.5481852,0.2309082,0.1064838,0.004440998,0.009202955,0.009470697,0.01481313],"genre_scores_gemma":[0.01922239,0.03578238,0.8409377,0.04561809,0.03177263,0.01119987,0.002699308,0.003529737,0.009237905],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8927925,"threshold_uncertainty_score":0.5669745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2614135022250905,"score_gpt":0.3635123270959036,"score_spread":0.1020988248708131,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}