{"id":"W3162563243","doi":"10.1111/eva.13253","title":"The interplay between hunting rate, hunting selectivity, and reproductive strategies shapes population dynamics of a large carnivore","year":2021,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii; Austrian Science Fund; Agence Nationale de la Recherche; Canada Research Chairs; Royal College of Nursing, Australia; Canada Excellence Research Chairs, Government of Canada; Biodiversa+; National Science Foundation","keywords":"Biology; Population; Carnivore; Ursus; Vital rates; Population growth; Offspring; Litter; Ecology; Population size; Reproductive success; Reproduction; Population model; Demography; Selection (genetic algorithm); Population decline; Reproductive value; Habitat; Predation","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003927704,0.00007589498,0.00009244838,0.0000187029,0.000744023,0.00002499198,0.00009734761,0.0000600157,0.00004766224],"category_scores_gemma":[0.0001161307,0.0000720016,0.00002657444,0.0003650369,0.0001524285,0.0003439482,0.0001686184,0.0001293013,0.00001199595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001089895,"about_ca_system_score_gemma":0.00003685244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003155551,"about_ca_topic_score_gemma":0.002760948,"domain_scores_codex":[0.9991337,0.0001174356,0.0002082831,0.0002975251,0.00009470723,0.0001483314],"domain_scores_gemma":[0.9993181,0.000282565,0.0001517739,0.0001782632,0.00004736668,0.00002189078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003342939,0.00003253526,0.9743109,0.000005729731,0.00001580313,1.568893e-7,0.00011265,0.000386553,0.0003455819,0.02267647,0.0001043843,0.00200588],"study_design_scores_gemma":[0.00006382171,0.000009715139,0.9729554,0.000005678331,0.0000193074,0.00000535059,0.0007710276,0.005348215,0.00004373993,0.01975715,0.000950374,0.00007021656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861301,0.000114998,0.009297152,0.00210178,0.00002355336,0.0002533107,0.00002778909,0.00003451774,0.002016848],"genre_scores_gemma":[0.9983507,0.00001755002,0.0009957685,0.00003423246,0.00006917427,0.0001091664,0.0001438705,0.000006445789,0.0002730284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01222071,"threshold_uncertainty_score":0.5722499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006663659727104997,"score_gpt":0.2574630466555587,"score_spread":0.2507993869284538,"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."}}