{"id":"W2288604827","doi":"10.1111/eva.12373","title":"Harvest‐induced evolution and effective population size","year":2016,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Academy of Finland","keywords":"Biology; Preharvest; Effective population size; Population; Population size; Ecology; Demography; Genetic variation; Botany","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001222376,0.00008559763,0.00006976481,0.00002638093,0.0002722877,0.00001293426,0.0001068774,0.00005753344,0.0026266],"category_scores_gemma":[0.00008282019,0.00006617518,0.00002529937,0.0002473433,0.0001387442,0.0003774132,0.0001680936,0.00006291284,0.0004795512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003211447,"about_ca_system_score_gemma":0.000008638573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005497874,"about_ca_topic_score_gemma":0.00005840436,"domain_scores_codex":[0.9991356,0.00005535661,0.0001250076,0.0002995501,0.0002014208,0.0001830723],"domain_scores_gemma":[0.9994168,0.0001962403,0.00004009487,0.0002365573,0.00001470421,0.00009561552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002165406,0.00007746669,0.7975537,0.000005222312,0.000008090861,4.282732e-7,0.00001812567,0.000005017671,0.01800524,0.01712912,0.002170568,0.1650054],"study_design_scores_gemma":[0.0001816615,0.00003656388,0.9337221,0.000002155673,0.000004464681,0.000007052077,0.000007472981,0.000123775,0.00004751725,0.01286669,0.05290452,0.00009603317],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7364281,0.00004898033,0.06664173,0.005289723,0.0000897342,0.002998173,0.00006332646,0.0002928027,0.1881474],"genre_scores_gemma":[0.9941206,0.00001879795,0.001158045,0.00003722142,0.00007247854,0.0007956729,0.00001286135,0.000009102727,0.003775221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2576925,"threshold_uncertainty_score":0.9982851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007097088756658253,"score_gpt":0.2381969669822853,"score_spread":0.2310998782256271,"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."}}