{"id":"W4404782122","doi":"10.5194/gmd-2024-126-rc2","title":"Comment on gmd-2024-126","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":"Statistics; Mathematics","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":[0.002507718,0.0011711,0.001143491,0.001251508,0.002671035,0.004910466,0.003199454,0.03230464,0.1578296],"category_scores_gemma":[0.01244133,0.0006037761,0.001997161,0.001729638,0.001735089,0.002743087,0.002046266,0.01497636,0.1318866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005112875,"about_ca_system_score_gemma":0.00587483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05523446,"about_ca_topic_score_gemma":0.05446712,"domain_scores_codex":[0.9978628,0.0001552084,0.0001428056,0.0002271492,0.001159992,0.0004520305],"domain_scores_gemma":[0.996541,0.0009116868,0.0001937703,0.0002809325,0.001626994,0.0004455563],"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":[0.00003462946,0.00001470803,0.00005617567,0.00004871308,0.000001718577,0.00005574637,0.00001059426,0.00002456985,0.00008805762,0.001064962,0.995912,0.002688173],"study_design_scores_gemma":[0.00002147903,0.00001156642,0.0005714613,0.00005913105,0.000002735723,0.00001410748,0.00002318042,0.00004255327,0.00008021578,0.0006732757,0.9984883,0.00001193731],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0009184956,0.002074168,0.0008304127,0.4095506,0.2163505,0.0007520058,0.02201455,0.003103547,0.3444058],"genre_scores_gemma":[0.00291904,0.0006801499,0.0006308632,0.5758878,0.01843597,0.0004891916,0.003260565,0.0005333702,0.3971631],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1578296,"threshold_uncertainty_score":0.5279926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02673241850364262,"score_gpt":0.3656795081084904,"score_spread":0.3389470896048478,"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."}}