{"id":"W6967239774","doi":"10.5061/dryad.66gc768","title":"Data from: Grizzly bear response to fine spatial and temporal scale spring snow cover in Western Alberta","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Snow; Habitat; Grizzly Bears; Scale (ratio); Akaike information criterion; Spring (device); Spatial ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003961091,0.0002440373,0.0001727536,0.0005501306,0.0006613661,0.0004513309,0.0005137711,0.0001854931,0.00155949],"category_scores_gemma":[0.0007486798,0.0001384996,0.0002162667,0.000856012,0.0002300336,0.0001361825,0.0002762862,0.000215096,0.0002839316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00494005,"about_ca_system_score_gemma":0.003217134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9675356,"about_ca_topic_score_gemma":0.9879037,"domain_scores_codex":[0.9997992,0.00001725478,0.00000862431,0.00004341668,0.0000889724,0.00004257376],"domain_scores_gemma":[0.9994746,0.00007737848,0.00008056193,0.00004155524,0.0002288424,0.00009702105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001744923,0.00005074773,0.9857823,0.00001768922,0.00006582908,0.00009384607,0.0005027386,0.003308309,0.0008412552,0.00007757433,0.002410624,0.006674679],"study_design_scores_gemma":[0.000008073561,0.0000135373,0.9957561,0.000004707385,0.00001442295,0.0000155274,0.0004123304,0.002359752,0.0001242492,0.00002657496,0.001258979,0.000005763693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9935202,0.00004906269,0.0002045213,0.00004153252,0.000003644804,0.00001380093,0.004948071,0.0000284831,0.001190687],"genre_scores_gemma":[0.9889319,0.00007824332,0.0005524651,0.00002781908,0.000002233709,0.00001931354,0.008001128,0.00001019451,0.002376631],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.03246444,"threshold_uncertainty_score":0.06531119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03077936127371959,"score_gpt":0.2826481490736067,"score_spread":0.2518687877998871,"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."}}