{"id":"W2132918676","doi":"10.1093/toxsci/kfm090","title":"Toward a Checklist for Exchange and Interpretation of Data from a Toxicology Study","year":2007,"lang":"en","type":"article","venue":"Toxicological Sciences","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greenfield Research (Canada)","funders":"National Institutes of Health","keywords":"Toxicogenomics; Checklist; Context (archaeology); Computer science; Data sharing; Annotation; Data science; Information retrieval; Data mining; Biology; Medicine; Artificial intelligence","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4016049,0.003931884,0.003799862,0.02727587,0.007435217,0.0165954,0.01282983,0.009763455,0.02169925],"category_scores_gemma":[0.4930151,0.004702649,0.004635303,0.01134213,0.007249969,0.02237263,0.01782987,0.01468476,0.02832172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01183298,"about_ca_system_score_gemma":0.07416178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007310903,"about_ca_topic_score_gemma":0.009055302,"domain_scores_codex":[0.6336281,0.1979517,0.1131677,0.007041194,0.04422018,0.003990954],"domain_scores_gemma":[0.2533819,0.2961653,0.0442954,0.09756194,0.2915595,0.01703584],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007977783,0.0009132537,0.00471119,0.01415837,0.0001800582,0.002813815,0.01369731,0.001769657,0.009065741,0.0547963,0.6274065,0.2696899],"study_design_scores_gemma":[0.000240089,0.0004787356,0.003140655,0.01530118,0.0001146201,0.0007273516,0.003642825,0.00121651,0.002881347,0.02201944,0.9499061,0.0003311283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005809629,0.003297555,0.7289869,0.08856265,0.01133763,0.07256211,0.0351591,0.019326,0.0349584],"genre_scores_gemma":[0.00652821,0.002803555,0.8931034,0.0170054,0.001910574,0.04065007,0.02562944,0.00246678,0.009902591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5983951,"threshold_uncertainty_score":0.7379277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1427779575458661,"score_gpt":0.3967305418508013,"score_spread":0.2539525843049352,"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."}}