{"id":"W4319233400","doi":"10.1101/2023.02.01.526335","title":"Climate, caribou and human needs linked by analysis of Indigenous and scientific knowledge","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; Yukon University; Université Laval; Environment and Climate Change Canada; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada; ArcticNet; Canada Research Chairs; Government of Canada; Parks Canada; Polar Knowledge Canada","keywords":"Circumpolar star; Indigenous; Geography; Tundra; Climate change; Traditional knowledge; Human welfare; Ecology; Environmental resource management; Ecosystem; Welfare; Environmental science; Political science; Oceanography; Biology","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":[0.007949105,0.0001405783,0.0002888085,0.003893506,0.001772947,0.003080542,0.000552549,0.0004534668,0.001753621],"category_scores_gemma":[0.02309447,0.0001802387,0.0002216519,0.003430682,0.003507621,0.001789406,0.003296515,0.0005700771,0.00006332774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002675501,"about_ca_system_score_gemma":0.004053612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05009979,"about_ca_topic_score_gemma":0.07084783,"domain_scores_codex":[0.9957919,0.002584621,0.0001730949,0.0003350409,0.0006961728,0.0004191616],"domain_scores_gemma":[0.9771872,0.01501251,0.004136152,0.0009369609,0.002006914,0.0007202701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005527516,0.0001310539,0.6910444,0.0002094587,0.00009737958,0.0002324405,0.2861044,0.0005448122,0.0007016244,0.003335573,0.0002582898,0.01728527],"study_design_scores_gemma":[0.000003811946,0.00006499374,0.5787504,0.000136304,0.00003687232,0.00008518371,0.4135462,0.001440887,0.0002427829,0.003485672,0.002185451,0.00002148503],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967145,0.00009824958,0.0002917815,0.0002865172,0.000002168679,0.00001717162,0.00005814648,0.000001460884,0.00253008],"genre_scores_gemma":[0.9995845,0.00004807369,0.0001978415,0.00001598336,0.000002461824,0.00001542509,0.00001889312,6.696404e-7,0.0001160569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05009979,"threshold_uncertainty_score":0.09961635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03718208511570163,"score_gpt":0.323722290993442,"score_spread":0.2865402058777404,"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."}}