{"id":"W6945631184","doi":"10.25545/xwgrbp/cdrudz","title":"WB_heterozygosity_vcf","year":2024,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Environment and Climate Change Canada; University of Manitoba; University of New Brunswick","funders":"","keywords":"Loss of heterozygosity; Inbreeding; Population; SNP; Selection (genetic algorithm)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001999098,0.003222452,0.002641403,0.004098214,0.001157202,0.003729197,0.003401392,0.00215817,0.1463325],"category_scores_gemma":[0.007934637,0.001446734,0.001648379,0.005929116,0.0005221651,0.001392,0.002167383,0.002244821,0.1769686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001065466,"about_ca_system_score_gemma":0.001993548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02094746,"about_ca_topic_score_gemma":0.02790934,"domain_scores_codex":[0.9985429,0.0002008006,0.0001354961,0.0006183474,0.0003169869,0.0001854833],"domain_scores_gemma":[0.997092,0.0009347291,0.0002465934,0.0008855577,0.0006514492,0.0001895153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009303948,0.00002957061,0.001462437,0.0008370156,0.0001034123,0.0000337534,0.00004975212,0.0005014833,0.0004962098,0.0005927131,0.9921852,0.003615468],"study_design_scores_gemma":[0.0003713199,0.00003061302,0.008713038,0.0003109284,0.0001066659,0.0001064734,0.00006402372,0.0009124177,0.001427453,0.003165271,0.9847133,0.00007851626],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001420603,0.00002551418,0.0001958993,0.00001625509,0.00001556128,0.000007482465,0.9981552,0.0008568501,0.000585191],"genre_scores_gemma":[0.0004580655,0.00002008637,0.000572339,0.00003279521,0.000005884081,0.0000623249,0.9975776,0.0005442966,0.0007265899],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8536675,"threshold_uncertainty_score":0.489531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02177272734616744,"score_gpt":0.2809778031777242,"score_spread":0.2592050758315568,"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."}}