{"id":"W6892212049","doi":"10.5061/dryad.073gb","title":"Data from: Coping with strong variations in winter severity: plastic habitat selection of deer at high density","year":2017,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Foraging; Habitat; Forage; Predation; Herbivore; Snow; Intraspecific competition","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":[0.0007406352,0.0003524657,0.000499798,0.001103269,0.0008598132,0.001605987,0.0007307867,0.0006124779,0.1123788],"category_scores_gemma":[0.003056182,0.0002339131,0.0002359771,0.002317748,0.0003526661,0.0006012964,0.0009286277,0.0006041635,0.03688606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322573,"about_ca_system_score_gemma":0.00254815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2131537,"about_ca_topic_score_gemma":0.3460568,"domain_scores_codex":[0.9994392,0.00003395688,0.00007023942,0.0001129467,0.0002566905,0.00008694886],"domain_scores_gemma":[0.9971598,0.0004346263,0.0003177658,0.0002775491,0.001517767,0.0002925582],"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":[0.001398743,0.0003218316,0.1912881,0.00140857,0.0001836908,0.0003724608,0.001296364,0.000375652,0.003261582,0.0005549861,0.6652411,0.134297],"study_design_scores_gemma":[0.0001739166,0.00008125609,0.5257498,0.0004859643,0.00008570829,0.0001214093,0.0007690356,0.0003583924,0.001411602,0.000265971,0.4704456,0.00005137725],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.07288996,0.0009624558,0.001043231,0.002479873,0.000393374,0.0003125115,0.8355103,0.0008392007,0.08556909],"genre_scores_gemma":[0.190277,0.00264726,0.003462096,0.001761654,0.0003047526,0.0006680911,0.6483113,0.0004794768,0.1520883],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2131537,"threshold_uncertainty_score":0.4238259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02477912071493368,"score_gpt":0.2681657489632244,"score_spread":0.2433866282482907,"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."}}