{"id":"W2171855901","doi":"","title":"How is the AI industry using the genomic tools in practice","year":2010,"lang":"en","type":"article","venue":"Bulletin - International Bull Evaluation Service/Interbull bulletin","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rogers Communications (Canada)","funders":"","keywords":"Genomic selection; Artificial insemination; Genotyping; Progeny testing; Biology; Selection (genetic algorithm); Genomic information; Biotechnology; Genetics; Genotype; Genome; Computer science; Single-nucleotide polymorphism; Artificial intelligence; Gene; Pregnancy","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":[0.09903649,0.001560897,0.001618052,0.005214206,0.006800739,0.03479622,0.005831087,0.01740351,0.01898365],"category_scores_gemma":[0.120115,0.001231135,0.001945123,0.005126601,0.02493298,0.04074572,0.009820912,0.01814476,0.02079441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007328948,"about_ca_system_score_gemma":0.02339378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109211,"about_ca_topic_score_gemma":0.006791274,"domain_scores_codex":[0.9370102,0.03186832,0.002737971,0.007503725,0.01649111,0.004388678],"domain_scores_gemma":[0.8234662,0.05604254,0.008328996,0.02453269,0.05850629,0.0291233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002437019,0.000858276,0.01700054,0.001631453,0.0002503504,0.0007853655,0.006302731,0.001643713,0.002226018,0.120424,0.2911983,0.5574355],"study_design_scores_gemma":[0.0000937095,0.000478486,0.006715658,0.004214271,0.00009567146,0.0007190814,0.01056355,0.001070895,0.001234515,0.1688531,0.8057461,0.0002149172],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004501705,0.0189326,0.02480991,0.9130419,0.006755443,0.0001326929,0.0001765982,0.000789794,0.03085946],"genre_scores_gemma":[0.1632697,0.07634674,0.1756555,0.5327374,0.01699671,0.0006976164,0.0008317078,0.001968896,0.03149568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09903649,"threshold_uncertainty_score":0.5237613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03550540171858847,"score_gpt":0.3209761019193377,"score_spread":0.2854707002007493,"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."}}