{"id":"W4281760743","doi":"10.1038/s41597-022-01381-8","title":"CAN-SAR: A database of Canadian species at risk information","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Carleton University; Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Listing (finance); Threatened species; Database; Computer science; Environmental resource management; Business; Ecology; Biology; Habitat; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008455794,0.00006573841,0.00006719158,0.0001737328,0.0009058629,0.00008363902,0.001118912,0.00001250946,0.2556742],"category_scores_gemma":[0.0001090645,0.00006689483,0.00001935866,0.001154209,0.0003096942,0.0005919847,0.002711992,0.00008175971,0.001672572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008258286,"about_ca_system_score_gemma":0.00005931726,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.147963,"about_ca_topic_score_gemma":0.5377956,"domain_scores_codex":[0.9987155,0.00004190433,0.0001784059,0.0002748183,0.0005378197,0.0002515114],"domain_scores_gemma":[0.9984173,0.00001315055,0.0001144453,0.001294465,0.00001060113,0.0001499981],"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":[0.000004826528,0.00001947822,0.0101546,0.00000412485,0.000002782976,0.000001631824,0.0003670263,0.00004189144,0.0009764142,0.0003971742,0.9873841,0.0006458875],"study_design_scores_gemma":[0.0001138958,0.000008346519,0.0315302,0.000001124992,0.000007320221,0.000003866655,0.002455147,0.0003952873,0.0004381053,0.0000173168,0.9649507,0.00007872499],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4426437,0.00003853131,0.00001756635,0.001283057,0.001397502,0.0002646043,0.4541672,0.0000305529,0.1001573],"genre_scores_gemma":[0.8543348,0.00005560427,0.0001403201,0.0003466688,0.00001518036,0.00001346848,0.13464,0.000007026685,0.01044687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4116911,"threshold_uncertainty_score":0.9991047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05533889582137173,"score_gpt":0.2347911153665203,"score_spread":0.1794522195451486,"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."}}