{"id":"W6958234002","doi":"10.60692/355tj-2nq58","title":"Asynchrony of actuarial and reproductive senescence: a lesson from an indeterminate grower","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Asynchrony (computer programming); Indeterminate; Fecundity; Oviparity; Senescence; Fertility","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":[0.0005873268,0.0001037904,0.0002099988,0.000345387,0.0002732745,0.0005380882,0.0002806714,0.0003789033,0.001386358],"category_scores_gemma":[0.001503944,0.0001229327,0.0001063205,0.0001011614,0.0006990793,0.0006127143,0.0005850978,0.0004201981,0.0001908659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002068009,"about_ca_system_score_gemma":0.0001534872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008060115,"about_ca_topic_score_gemma":0.001351178,"domain_scores_codex":[0.9998991,0.00001958319,0.000006622743,0.00004017956,0.0000189094,0.00001539308],"domain_scores_gemma":[0.9991013,0.0002766772,0.0002666446,0.0001307323,0.00005847591,0.0001662402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001004443,0.0001955539,0.6683578,0.0001495915,0.00007309143,0.003112655,0.004562301,0.002669916,0.2245996,0.02006854,0.001117939,0.0740886],"study_design_scores_gemma":[0.00001143461,0.0002607615,0.9782766,0.00002195496,0.00002082821,0.001495383,0.0007141953,0.003649907,0.004479756,0.008115075,0.002928842,0.00002542297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949439,0.0003180397,0.001808939,0.0002809719,0.00001048325,0.000003871733,0.00003979082,0.00001834205,0.002575711],"genre_scores_gemma":[0.9990224,0.000069531,0.0003887721,0.00003441329,0.000008998593,0.000001876854,0.00001924018,0.00000421458,0.000450571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001386358,"threshold_uncertainty_score":0.004637778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04266336023597722,"score_gpt":0.2147097668326401,"score_spread":0.1720464065966629,"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."}}