{"id":"W6995858288","doi":"","title":"Predicting coastal cutthroat trout molt productive capacity from physiographic variables","year":2016,"lang":"en","type":"other","venue":"VIUSpace (Vancouver Island University Library)","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"California Department of Fish and Wildlife; Fisheries and Oceans Canada; Ministry of Environment; Washington Department of Fish and Wildlife; Royal Roads University; Ministry of Forests, Lands and Natural Resource Operations; Washington State University","keywords":"Fish migration; Abundance (ecology); Habitat; Trout; Watershed; Alewife; Channel (broadcasting); Oncorhynchus","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003782126,0.0004272213,0.0004360821,0.0001985601,0.0003237052,0.00002468129,0.0005094352,0.0002972053,0.01939526],"category_scores_gemma":[0.00001148543,0.0003737732,0.000139206,0.0003370531,0.0006060005,0.0008431718,0.001083863,0.0002702738,0.0004640202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000729982,"about_ca_system_score_gemma":0.00002062859,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003925128,"about_ca_topic_score_gemma":0.6133769,"domain_scores_codex":[0.9981782,0.0001240479,0.000117031,0.0008573252,0.0002690363,0.0004542966],"domain_scores_gemma":[0.9991081,0.00007406963,0.0002639388,0.0004432583,0.000005140684,0.0001055361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005814814,0.00009165815,0.06087735,0.00002350459,0.0003520239,0.00003494316,0.0002882137,0.00001088114,0.00001982758,0.00008017781,0.9381012,0.00006209454],"study_design_scores_gemma":[0.0009550161,0.00006479836,0.01325386,0.0001224129,0.0002013552,2.888137e-7,0.0005650527,0.00001699963,0.0000550976,0.0007112018,0.9835143,0.0005396141],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003668853,0.00002309362,0.0003732908,0.0005212728,0.0008879245,0.0005031443,0.0008849177,0.0004697179,0.9926678],"genre_scores_gemma":[0.006990535,0.0005379519,0.0007517167,0.0001802474,0.0003352874,0.00000362593,0.00004188548,0.0001576757,0.9910011],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6094518,"threshold_uncertainty_score":0.9998714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004724582598437178,"score_gpt":0.1584771837969983,"score_spread":0.1537526011985611,"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."}}