{"id":"W6929440997","doi":"10.5061/dryad.j6q573nh4","title":"Evidence for synergistic cumulative impacts of marking and hunting in a wildlife species.","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Université Laval","funders":"","keywords":"Population; Limiting; Ectotherm; Work (physics)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001639224,0.00037064,0.0005676527,0.001067188,0.0003852948,0.000982554,0.0006215803,0.0005941831,0.001850308],"category_scores_gemma":[0.002572576,0.0004167598,0.0008828587,0.0005672895,0.0009117415,0.0006252475,0.001915055,0.0006145234,0.0002403679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003655677,"about_ca_system_score_gemma":0.0003521847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002904291,"about_ca_topic_score_gemma":0.009709339,"domain_scores_codex":[0.9988997,0.0002570729,0.00008389993,0.0004264766,0.0002260695,0.0001067931],"domain_scores_gemma":[0.9945028,0.001349671,0.002136463,0.0007624447,0.0004744945,0.0007741757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003264504,0.00008274466,0.9681761,0.0001078046,0.0010319,0.0001876579,0.0002425525,0.0004893106,0.01769114,0.0001155234,0.0001724894,0.01137626],"study_design_scores_gemma":[0.000002226171,0.0001669429,0.9988896,0.000005710227,0.00008114534,0.0001272525,0.00009990724,0.000276187,0.0001568838,0.00006625493,0.0001221407,0.000005690938],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.996496,0.001565596,0.0006146171,0.0001304301,0.00001594851,0.000007938663,0.0001942582,0.0000218534,0.0009534577],"genre_scores_gemma":[0.9986839,0.0002480856,0.0004835238,0.00007099871,0.00001387248,0.000009314176,0.0001853765,0.00000458971,0.0003002583],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.002904291,"threshold_uncertainty_score":0.008669138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1083048015711456,"score_gpt":0.3145109915768704,"score_spread":0.2062061900057248,"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."}}