{"id":"W6939802961","doi":"10.6084/m9.figshare.19375715.v1","title":"Collating life history and habitat information from multiple online data repositories for vertebrate species in Canada","year":2022,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Habitat; Abiotic component; Life history; Variety (cybernetics); Vertebrate; Taxonomic rank; Life history theory; Fish <Actinopterygii>","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001071576,0.0008005771,0.000711843,0.01169218,0.002556235,0.002733512,0.00197408,0.0005494878,0.02882064],"category_scores_gemma":[0.009528739,0.0006044829,0.0008878916,0.02472791,0.0006080151,0.001162841,0.002206292,0.0007416349,0.008388815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01193307,"about_ca_system_score_gemma":0.02948757,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9675359,"about_ca_topic_score_gemma":0.9869941,"domain_scores_codex":[0.9987416,0.00006219657,0.0001101263,0.0003457742,0.0005140514,0.00022626],"domain_scores_gemma":[0.9917623,0.001210571,0.0005108342,0.0007529635,0.005067481,0.0006959068],"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":[0.0002896652,0.00005453892,0.1099744,0.002772795,0.0003912784,0.000383863,0.001967157,0.003219496,0.001509363,0.006933582,0.7825084,0.0899955],"study_design_scores_gemma":[0.00006563094,0.00001607303,0.2121226,0.00114684,0.0001963988,0.0001695113,0.001255041,0.003400918,0.001532101,0.002164742,0.7777504,0.0001796607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005163932,0.0002483479,0.001078709,0.0001363456,0.00001832185,0.00004006128,0.987677,0.0007636991,0.004873588],"genre_scores_gemma":[0.0274785,0.0004795223,0.007023417,0.0001233298,0.00001220887,0.0001495177,0.9601458,0.0004134948,0.004174146],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03246409,"threshold_uncertainty_score":0.09641463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08488063543535553,"score_gpt":0.2380981217070105,"score_spread":0.153217486271655,"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."}}