{"id":"W3034603929","doi":"10.1111/faf.12477","title":"Mesohabitat modelling in fish ecology: A global synthesis","year":2020,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mesoscale meteorology; River ecosystem; Habitat; Ecology; Fish <Actinopterygii>; Process (computing); Environmental resource management; Linkage (software); Relevance (law); Computer science; Environmental science; Geography; Fishery; Biology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.002656005,0.001044923,0.001611311,0.002590654,0.0003148636,0.002072411,0.001009369,0.0009459227,0.004756541],"category_scores_gemma":[0.003152389,0.0004317274,0.001429975,0.004419446,0.0009963918,0.002027171,0.001957329,0.001440312,0.0003868754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001451224,"about_ca_system_score_gemma":0.001572897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01400156,"about_ca_topic_score_gemma":0.009784855,"domain_scores_codex":[0.9995379,0.0002397476,0.00003634375,0.00008450273,0.00006823344,0.00003325842],"domain_scores_gemma":[0.9975584,0.001689935,0.000181456,0.0002551855,0.0002421286,0.00007288581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0001263766,0.0001246091,0.01408268,0.009305373,0.001494868,0.0002151109,0.0007531336,0.3662517,0.001140867,0.2155346,0.01478045,0.3761903],"study_design_scores_gemma":[0.00005535761,0.0002733795,0.05048978,0.01706459,0.002093545,0.0002573355,0.001109922,0.4051746,0.000979819,0.3220879,0.2002498,0.0001639815],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.06310098,0.7535812,0.1349626,0.0201132,0.0008495358,0.00005324502,0.001473562,0.0004168969,0.02544873],"genre_scores_gemma":[0.4471584,0.5088781,0.03809433,0.001207746,0.001127125,0.0001180013,0.000698845,0.0001855681,0.002531857],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01400156,"threshold_uncertainty_score":0.02784008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582132540406039,"score_gpt":0.1898180157603752,"score_spread":0.1739966903563148,"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."}}