{"id":"W2079420003","doi":"10.1002/hed.21311","title":"Integrative molecular characterization of head and neck cancer cell model genomes","year":2009,"lang":"en","type":"article","venue":"Head & Neck","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; University of British Columbia; BC Cancer Agency","funders":"National Institute of Dental and Craniofacial Research; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Characterization (materials science); Genome; Head and neck cancer; Computational biology; Biology; Cancer; Evolutionary biology; Genetics; Nanotechnology; Gene; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00002920098,0.00012104,0.0001378197,0.00001865009,0.00003735908,0.00001386174,0.00006957793,0.00008072644,0.00002250752],"category_scores_gemma":[0.000003449916,0.0001103841,0.00004505907,0.00003899404,0.00002838025,0.000008070843,0.00002918804,0.00003977227,0.000001289299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001509576,"about_ca_system_score_gemma":0.0000680165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007002747,"about_ca_topic_score_gemma":0.00006091015,"domain_scores_codex":[0.9994219,0.00001839422,0.0001696927,0.0001919999,0.00005981593,0.0001381798],"domain_scores_gemma":[0.9996406,0.000001539818,0.00007718037,0.0001560077,0.00007821189,0.00004650535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003623762,0.00005908502,0.001380039,0.00002518374,0.00001549276,7.730203e-7,0.0004674752,0.0002205808,0.9958557,0.0007068604,0.0000400384,0.001192568],"study_design_scores_gemma":[0.0008670446,0.0006257234,0.03276773,0.00005305148,0.00003806081,0.000008288267,0.0001887934,0.003267081,0.9568222,0.0006447078,0.004400315,0.0003170161],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948158,0.001684259,0.001347824,0.0001845058,0.00003008489,0.0001214051,0.00007883873,0.000006445702,0.001730841],"genre_scores_gemma":[0.996206,0.001226576,0.001005259,0.0003716805,0.00004988466,0.00001280268,0.0001594695,0.00001007038,0.0009582832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03903348,"threshold_uncertainty_score":0.4501332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008306030653732144,"score_gpt":0.2406030716972944,"score_spread":0.2322970410435623,"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."}}