{"id":"W6923095894","doi":"10.1371/journal.pone.0115535.t003","title":"Summary of sample sizes of events (&lt;i&gt;n&lt;/i&gt;) and transition probabilities (&lt;i&gt;p&lt;/i&gt;) from multi-state model reproductive analysis of grizzly bears in Alberta, Canada.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sample (material); Grizzly Bears; Sample size determination; Statistical model; Statistical analysis; Reproduction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001518454,0.001459049,0.001464427,0.002110744,0.001507068,0.001562718,0.003723999,0.001612842,0.03019464],"category_scores_gemma":[0.0102842,0.0007036894,0.001501921,0.003850095,0.0007108004,0.0005971939,0.001000338,0.001467697,0.01299169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006844241,"about_ca_system_score_gemma":0.01402572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8613445,"about_ca_topic_score_gemma":0.9321868,"domain_scores_codex":[0.9992443,0.00007642504,0.0000613314,0.0002912508,0.00020201,0.0001246408],"domain_scores_gemma":[0.9960496,0.001446427,0.000176656,0.000469859,0.001552472,0.0003049682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001300901,0.0000308515,0.01038169,0.000775905,0.0001653048,0.00004032883,0.00005062538,0.001407759,0.0001306203,0.0004595862,0.9814185,0.005008719],"study_design_scores_gemma":[0.001711092,0.00004551873,0.1493976,0.001642852,0.0008489462,0.0002380793,0.0005413591,0.00491761,0.0008456711,0.00420103,0.835444,0.0001662956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007333909,0.0002188689,0.0001338218,0.00006923794,0.00002692848,0.0000170952,0.9980568,0.0001742774,0.0005694502],"genre_scores_gemma":[0.004299752,0.0001321981,0.0005170436,0.00007624037,0.000009150568,0.00006954461,0.9936398,0.00006444645,0.001191876],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1386555,"threshold_uncertainty_score":0.2789442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0293537520474975,"score_gpt":0.2411721524784506,"score_spread":0.2118184004309531,"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."}}