{"id":"W7028470972","doi":"","title":"Exploring the factors that contribute to successful battles with cancer","year":2022,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Diverse Interdisciplinary Research Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cancer; Public health; Biomedicine; MEDLINE; Alternative medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002302992,0.0002952615,0.000276435,0.0007257056,0.002781352,0.004461553,0.0005413394,0.0008101939,0.03254811],"category_scores_gemma":[0.01887487,0.0001895151,0.0003022446,0.001004806,0.002008735,0.00133009,0.001925877,0.001853279,0.003996446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338011,"about_ca_system_score_gemma":0.003982966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009892448,"about_ca_topic_score_gemma":0.03800672,"domain_scores_codex":[0.9986702,0.0006302592,0.00003584178,0.00008175368,0.0002365903,0.0003454517],"domain_scores_gemma":[0.9927496,0.002617378,0.001292648,0.0001601963,0.0008038759,0.002376202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005661696,0.0007569368,0.3171914,0.0009786793,0.0001715967,0.001243618,0.01447618,0.0003356213,0.0009175717,0.008833238,0.2828137,0.3717153],"study_design_scores_gemma":[0.00005328501,0.0003826025,0.5816915,0.001209263,0.0002266415,0.002148016,0.1102842,0.0004616885,0.001241662,0.01717682,0.2850231,0.0001011729],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4973844,0.03785739,0.001786992,0.2172651,0.003344411,0.0002479992,0.001336429,0.000265625,0.2405116],"genre_scores_gemma":[0.8990974,0.03421363,0.002164748,0.01266663,0.000888784,0.000150326,0.0006324839,0.0002031898,0.0499828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03254811,"threshold_uncertainty_score":0.1088842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02943869457499332,"score_gpt":0.2318342048241523,"score_spread":0.202395510249159,"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."}}