{"id":"W4309855372","doi":"10.3390/curroncol29120715","title":"A Novel, Simple, and Low-Cost Approach for Machine Learning Screening of Kidney Cancer: An Eight-Indicator Blood Test Panel with Predictive Value for Early Diagnosis","year":2022,"lang":"en","type":"article","venue":"Current Oncology","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sun Yat-sen University","keywords":"Medicine; Renal cell carcinoma; Receiver operating characteristic; Stage (stratigraphy); Cancer; Kidney cancer; Internal medicine; Oncology; Clear cell renal cell carcinoma","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001882094,0.001294277,0.001162266,0.001322895,0.000337522,0.0007347675,0.001058182,0.0009333832,0.0006977913],"category_scores_gemma":[0.002675049,0.0003323279,0.0007576871,0.0008935013,0.0002174159,0.0007957523,0.0006531713,0.0009868785,0.0005923178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003225026,"about_ca_system_score_gemma":0.0009952598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00279897,"about_ca_topic_score_gemma":0.003458388,"domain_scores_codex":[0.9991418,0.0002614429,0.00005995819,0.0002073763,0.0002361742,0.0000932584],"domain_scores_gemma":[0.9992176,0.0003139433,0.0001082048,0.00005283484,0.0002480288,0.00005940018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001296616,0.001472264,0.1471832,0.0005027563,0.0007036335,0.0007484995,0.0001260028,0.1049229,0.04931794,0.001253901,0.008534285,0.6839381],"study_design_scores_gemma":[0.00009930717,0.0007027935,0.02293898,0.00004259255,0.0003497999,0.0006075996,0.0000281983,0.9622971,0.008749706,0.001473911,0.002635245,0.0000745992],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1664785,0.002094087,0.8251401,0.000701397,0.0002040413,0.000365285,0.001007839,0.002130896,0.001877921],"genre_scores_gemma":[0.7876729,0.0006898168,0.2084927,0.0002816539,0.0002151564,0.0003238411,0.001267152,0.00003196697,0.001024879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00279897,"threshold_uncertainty_score":0.009953558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09208782708092689,"score_gpt":0.3419126300789336,"score_spread":0.2498248029980067,"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."}}