{"id":"W6977001336","doi":"10.6084/m9.figshare.22814312.v1","title":"Data and R Code for Estimates of life history parameters in a high latitude, arid- country vervet monkey population","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Life history; Population; Code (set theory); Vervet monkey; Life history theory","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":[0.002054012,0.001750233,0.001744348,0.002750284,0.0009871935,0.001945823,0.002667714,0.001902699,0.1934443],"category_scores_gemma":[0.01137957,0.0009913218,0.00154824,0.005379595,0.0006102531,0.0008500565,0.001544202,0.001643565,0.1244318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347856,"about_ca_system_score_gemma":0.002515927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02662329,"about_ca_topic_score_gemma":0.04032788,"domain_scores_codex":[0.9986745,0.0002860365,0.0001859403,0.0003746859,0.0002834102,0.0001953263],"domain_scores_gemma":[0.9942614,0.002580038,0.0005764281,0.001288388,0.0009084652,0.0003853067],"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":[0.00007155891,0.00002211055,0.001405527,0.0005042059,0.00006691418,0.00002736767,0.00003871969,0.0006350724,0.0002310313,0.0008354738,0.9938982,0.002263718],"study_design_scores_gemma":[0.0009003498,0.00003335823,0.01547899,0.0004268812,0.0001222175,0.0001071662,0.0000748236,0.0009207542,0.0005571764,0.005285612,0.9760049,0.00008772828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001240517,0.00001567228,0.0002670157,0.00003632973,0.00001444117,0.00002247883,0.9986616,0.000396331,0.0004619757],"genre_scores_gemma":[0.000906674,0.00003633518,0.001829215,0.0001440608,0.00001004001,0.0005841728,0.9947702,0.000547016,0.001172338],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1934443,"threshold_uncertainty_score":0.6471357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1515136731482006,"score_gpt":0.3497804043866445,"score_spread":0.1982667312384438,"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."}}