{"id":"W2615194926","doi":"10.1007/s11160-017-9477-y","title":"Designing a global assessment of climate change on inland fishes and fisheries: knowns and needs","year":2017,"lang":"en","type":"article","venue":"Reviews in Fish Biology and Fisheries","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Chinese Academy of Sciences; U.S. Fish and Wildlife Service; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey; European Commission; Sight Research UK; Natural Environment Research Council; University of Missouri","keywords":"Climate change; Fishery; Fisheries management; Environmental resource management; Livelihood; Scale (ratio); Adaptive capacity; Geography; Environmental planning; Biology; Ecology; Fishing; Environmental science","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":[0.01780066,0.001553873,0.001813603,0.00233574,0.00123268,0.005802431,0.001679333,0.002410276,0.004163219],"category_scores_gemma":[0.02722337,0.0006269938,0.001506752,0.003026485,0.001785747,0.009428871,0.004118679,0.001587393,0.0005127276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002356363,"about_ca_system_score_gemma":0.008302717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02426467,"about_ca_topic_score_gemma":0.05221245,"domain_scores_codex":[0.9945971,0.003516883,0.0004987353,0.0004419501,0.0005942848,0.0003511022],"domain_scores_gemma":[0.9875453,0.00671923,0.001632096,0.0008032204,0.002587025,0.0007130683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005423931,0.0004145755,0.1775863,0.008636125,0.003315745,0.0004383357,0.001838148,0.1723899,0.007499269,0.04593219,0.01565248,0.5657545],"study_design_scores_gemma":[0.000255308,0.001465857,0.257522,0.01007376,0.003937304,0.0004414189,0.03387458,0.1819956,0.01124977,0.3764656,0.1220161,0.0007028698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.3611003,0.1105945,0.3602878,0.07672158,0.003713481,0.001843289,0.00711402,0.0008384498,0.07778653],"genre_scores_gemma":[0.6483447,0.05986843,0.2827837,0.00299253,0.0007945574,0.0007312166,0.001565741,0.0002686368,0.002650554],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02426467,"threshold_uncertainty_score":0.09413999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04826853862140646,"score_gpt":0.3124474571536822,"score_spread":0.2641789185322757,"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."}}