{"id":"W3047989485","doi":"10.1002/cncr.33114","title":"Development and validation of a Surgical Prioritization and Ranking Tool and Navigation Aid for Head and Neck Cancer (SPARTAN‐HN) in a scarce resource setting: Response to the COVID‐19 pandemic","year":2020,"lang":"en","type":"article","venue":"Cancer","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sinai Health System; Sunnybrook Health Science Centre; Western University; McMaster University; University Health Network; University of Toronto; Dalhousie University; Princess Margaret Cancer Centre; Public Health Ontario","funders":"National Cancer Institute","keywords":"Medicine; Triage; Ranking (information retrieval); Rank correlation; Pandemic; Delphi method; Spearman's rank correlation coefficient; Head and neck; Head and neck cancer; Coronavirus disease 2019 (COVID-19); Cancer; Surgery; Disease; Medical emergency; Machine learning; Internal medicine; Artificial intelligence; Computer science","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":[0.07750235,0.0008253897,0.0007628916,0.002428832,0.0009706288,0.001680922,0.001590826,0.000804189,0.001510088],"category_scores_gemma":[0.09385774,0.0003963165,0.001143157,0.001293258,0.0009762481,0.001312596,0.002254756,0.001090161,0.0003265394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003288874,"about_ca_system_score_gemma":0.008483338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004258502,"about_ca_topic_score_gemma":0.007348946,"domain_scores_codex":[0.9570929,0.02945075,0.003945862,0.001613378,0.006968771,0.0009283811],"domain_scores_gemma":[0.928486,0.04149186,0.004711273,0.002339161,0.0214989,0.001472868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002227646,0.003427855,0.234691,0.002588251,0.0004615306,0.0006593132,0.02256206,0.03348975,0.007383409,0.0025537,0.01544717,0.6745083],"study_design_scores_gemma":[0.002486163,0.01800495,0.4883389,0.003633414,0.0008406722,0.00196078,0.04605616,0.3583622,0.02531316,0.007597981,0.0465739,0.0008318295],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9072226,0.0002502605,0.06971805,0.001407439,0.0001897154,0.01436229,0.0006830073,0.0003561902,0.005810583],"genre_scores_gemma":[0.63416,0.0002732046,0.3542963,0.0004005893,0.00004716129,0.008467892,0.001459145,0.00005078143,0.0008449266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07750235,"threshold_uncertainty_score":0.4098765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06441888983932038,"score_gpt":0.3639874977129942,"score_spread":0.2995686078736738,"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."}}