{"id":"W4214547161","doi":"10.1111/eva.13364","title":"Pedigree analysis and estimates of effective breeding size characterize sea lamprey reproductive biology","year":2022,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University","funders":"Great Lakes Fishery Commission","keywords":"Biology; Lamprey; Spawn (biology); Pedigree chart; Population; Petromyzon; Ecology; Zoology; Fishery; Effective population size; Demography; Genetic variation; Genetics","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":[0.0008360955,0.0001479792,0.0001217503,0.00142149,0.0001595292,0.000287912,0.0001547606,0.0001018469,0.0007594361],"category_scores_gemma":[0.002046787,0.00009731416,0.0001445661,0.0004963911,0.0001276099,0.0002947317,0.0002154953,0.0001049639,0.0001391439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002821637,"about_ca_system_score_gemma":0.0001724706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007097752,"about_ca_topic_score_gemma":0.02014258,"domain_scores_codex":[0.9998215,0.0000760209,0.00001415378,0.00004639873,0.00003068404,0.00001132464],"domain_scores_gemma":[0.998956,0.000355473,0.0004000711,0.00008439404,0.0001509549,0.00005299219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000413546,0.00001659624,0.9665009,0.00001973481,0.00005911403,0.00005191572,0.0001183466,0.003799971,0.007515979,0.0002093475,0.0001748702,0.02149188],"study_design_scores_gemma":[0.000002727506,0.00003645779,0.9853525,0.000005736455,0.00002082315,0.00008151806,0.00005820441,0.01332533,0.0006231515,0.000208204,0.0002789916,0.000006311004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934648,0.00007373345,0.005735389,0.000009997388,8.792153e-7,0.000007697385,0.0003055627,0.00003249627,0.0003695371],"genre_scores_gemma":[0.9957641,0.00005223322,0.00357986,0.000006855743,0.000001856828,0.000008350949,0.0004192015,0.000005751934,0.0001616368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007097752,"threshold_uncertainty_score":0.01411289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006294746149990964,"score_gpt":0.2274478737942262,"score_spread":0.2211531276442353,"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."}}