{"id":"W4403869916","doi":"10.5194/sp-2024-9-rc2","title":"Comment on sp-2024-9","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"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":[0.003881576,0.0008350871,0.001062617,0.001662361,0.003412787,0.004804478,0.0027529,0.02203372,0.2250051],"category_scores_gemma":[0.03265626,0.0005138921,0.001512212,0.001641506,0.00165742,0.00297322,0.002228242,0.01116638,0.1973288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003453051,"about_ca_system_score_gemma":0.004535294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0212737,"about_ca_topic_score_gemma":0.02709864,"domain_scores_codex":[0.9964378,0.0003000828,0.0003582828,0.0003627001,0.001956756,0.0005844198],"domain_scores_gemma":[0.9860595,0.003228423,0.0004971228,0.0009230916,0.007598798,0.001693062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001443728,0.000004274893,0.00004030023,0.00003185919,0.000001162428,0.00005281339,0.000007853537,0.000004935279,0.00003215007,0.0004376841,0.9975421,0.00183035],"study_design_scores_gemma":[0.00001300949,0.000008198584,0.0003824869,0.00007792737,0.000001893412,0.00002838798,0.0000287467,0.00002534331,0.00006192196,0.000410116,0.9989532,0.00000876239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005336454,0.001215986,0.0007448773,0.4084284,0.3961977,0.0005762886,0.006868128,0.002451636,0.1829833],"genre_scores_gemma":[0.003329485,0.001039437,0.0005145292,0.4098106,0.06496269,0.0005898325,0.002561967,0.0008509459,0.5163405],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2250051,"threshold_uncertainty_score":0.7527172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02688487755783025,"score_gpt":0.3643419248972721,"score_spread":0.3374570473394418,"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."}}