{"id":"W6923137643","doi":"10.1371/journal.pone.0115535.t001","title":"Known fate survival analysis model selection results of grizzly bears in Alberta, Canada.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grizzly Bears; Selection (genetic algorithm); Survival analysis; Population; Population viability analysis; Statistical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002186745,0.0002989973,0.000630676,0.0008506156,0.00005821036,0.00005025449,0.002735611,0.0003630989,0.0003359687],"category_scores_gemma":[0.002312504,0.000324821,0.000113026,0.002179506,0.0000133557,0.0001559715,0.0007596734,0.0005231308,0.00009203633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006448817,"about_ca_system_score_gemma":0.002446055,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4874942,"about_ca_topic_score_gemma":0.9594013,"domain_scores_codex":[0.9975626,0.0001035667,0.0005609051,0.0006921726,0.0007127316,0.0003680343],"domain_scores_gemma":[0.9974826,0.0002383244,0.0005472607,0.001287847,0.0003558114,0.00008815695],"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":[0.000006065592,0.0000203078,0.000002156522,0.0000523626,0.00005790917,0.00001253646,0.00002944207,0.03334048,2.270327e-7,0.000003949596,0.9660411,0.0004334736],"study_design_scores_gemma":[0.0001707698,0.00002904683,0.00009226664,0.0002721457,0.00003404199,0.000001497446,0.000002090436,0.1471751,0.00001507925,0.00004366639,0.8518708,0.0002933809],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001046026,0.00007407538,0.00008754245,0.0001468257,0.0001472046,0.0001340245,0.9990957,0.0001002506,0.0002039043],"genre_scores_gemma":[0.0005604457,0.000002349683,0.001172292,0.00002653415,0.0000278116,0.00002590976,0.9978863,0.000009990344,0.0002883743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4719071,"threshold_uncertainty_score":0.9999204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03870659521041737,"score_gpt":0.2524550517303977,"score_spread":0.2137484565199804,"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."}}