{"id":"W2620614147","doi":"","title":"Robust Statistical Approaches for Sib-Pair Linkage Analysis of Quantitative Trait Loci","year":2008,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"","keywords":"Linkage (software); Quantitative trait locus; Trait; Computer science; Genetic linkage; Statistical analysis; Computational biology; Genetics; Artificial intelligence; Biology; Statistics; Mathematics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005953379,0.0003979052,0.001187141,0.000360914,0.0002145035,0.0001160712,0.0009248155,0.0003744665,0.0002264366],"category_scores_gemma":[0.02091429,0.0003885376,0.0005008064,0.0006749086,0.000623746,0.00005307999,0.0005636052,0.0005884212,0.000003986368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008487021,"about_ca_system_score_gemma":0.0002746466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003525001,"about_ca_topic_score_gemma":0.000412059,"domain_scores_codex":[0.9921924,0.004992696,0.001086047,0.0008446363,0.0005017709,0.0003823981],"domain_scores_gemma":[0.9715648,0.02353303,0.000893556,0.001576105,0.002238273,0.0001942481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002830941,0.0007533129,0.0003276599,0.000633292,0.0009095647,0.000002362523,0.006627322,0.0004982466,0.00006913287,0.969366,0.0009727999,0.01981197],"study_design_scores_gemma":[0.0005586028,0.00000325478,0.005225434,0.000769758,0.001665545,0.000002240231,0.0004313785,0.6362213,0.003722257,0.3501643,0.0006077929,0.0006280363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01609292,0.0001974511,0.96877,0.0009213555,0.00006720721,0.0007026151,0.002483784,0.0001069759,0.0106577],"genre_scores_gemma":[0.1248916,0.0001296369,0.8725932,0.0000213763,0.00001192938,0.0001511658,0.001093851,0.00004831218,0.001058979],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6357231,"threshold_uncertainty_score":0.9998567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1835846592503944,"score_gpt":0.3415130075281886,"score_spread":0.1579283482777943,"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."}}