{"id":"W6982525266","doi":"","title":"Integration strategies to identify candidate genes in rodent models of human alcoholism.","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Candidate gene; Gene; Drug candidate; Genome; Rodent","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003548022,0.001220989,0.001551525,0.006338579,0.001085021,0.001530173,0.00188934,0.001328923,0.0164543],"category_scores_gemma":[0.002252097,0.00104495,0.001924802,0.002387966,0.001153105,0.001032399,0.00293365,0.003735798,0.003633438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000793142,"about_ca_system_score_gemma":0.001079257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001533138,"about_ca_topic_score_gemma":0.005477142,"domain_scores_codex":[0.99778,0.0006652421,0.000180195,0.000464976,0.0005958552,0.0003136698],"domain_scores_gemma":[0.9980275,0.0005940957,0.0004099806,0.0003646171,0.0002466225,0.0003570957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004008525,0.002163635,0.006506391,0.001106561,0.0009516365,0.001113952,0.0004593419,0.0008178696,0.8483791,0.02239797,0.01002988,0.1020651],"study_design_scores_gemma":[0.005033741,0.01287499,0.06393091,0.0009538228,0.006789007,0.006277267,0.001182961,0.01155377,0.6327367,0.02118592,0.2371466,0.0003342694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3588294,0.0190365,0.5291348,0.004985725,0.002604613,0.008928336,0.02711707,0.003839341,0.04552418],"genre_scores_gemma":[0.3423693,0.01576391,0.5258184,0.003810096,0.0004884358,0.0184073,0.02438399,0.002662549,0.06629606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0164543,"threshold_uncertainty_score":0.05504513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05085383836676135,"score_gpt":0.3567577385561446,"score_spread":0.3059039001893833,"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."}}