{"id":"W1973726295","doi":"10.1063/1.3275632","title":"Bayesian Inference of Tumor Hypoxia","year":2009,"lang":"lt","type":"article","venue":"AIP conference proceedings","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fields Institute for Research in Mathematical Sciences; University of Waterloo","funders":"","keywords":"Immunohistochemistry; Hypoxia (environmental); Pathology; Tumor hypoxia; Biopsy; Biomarker; Biology; Medicine; Cancer research; Internal medicine; Radiation therapy; Chemistry","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":[0.007619191,0.001079946,0.002330922,0.002220809,0.001040558,0.002402829,0.002074185,0.00186506,0.003490453],"category_scores_gemma":[0.0346357,0.001046347,0.001498175,0.001084982,0.002088746,0.002344122,0.001897289,0.003176869,0.0008172344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00211577,"about_ca_system_score_gemma":0.001652037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006093183,"about_ca_topic_score_gemma":0.005304068,"domain_scores_codex":[0.9970621,0.0014441,0.0001291454,0.0007727573,0.0003638635,0.0002279848],"domain_scores_gemma":[0.9774674,0.01925018,0.001090314,0.0007051146,0.001141892,0.0003450873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006254227,0.00009182774,0.01403077,0.0003105145,0.00033762,0.0002361576,0.0002416934,0.8450603,0.002367995,0.05824829,0.004372786,0.07407665],"study_design_scores_gemma":[0.0000449781,0.00004438978,0.002365411,0.0000646374,0.00004100727,0.00007793339,0.00002984825,0.9356577,0.0007484043,0.05993174,0.0009561143,0.0000379021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.052271,0.001025696,0.9420893,0.000966854,0.00007946786,0.0001110192,0.0006688056,0.0002586547,0.002529187],"genre_scores_gemma":[0.8244779,0.001530754,0.165252,0.0007181303,0.0004234662,0.0004712394,0.003372599,0.000201051,0.003552923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007619191,"threshold_uncertainty_score":0.04029459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01390503116529028,"score_gpt":0.2555676243960733,"score_spread":0.241662593230783,"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."}}