{"id":"W6960891718","doi":"10.1371/journal.pone.0248643.g004","title":"Fig 4 -","year":2021,"lang":"en","type":"other","venue":"Figshare","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Medical imaging; Confidence interval; Computed tomography; Modality (human–computer interaction)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008093494,0.0006735907,0.0003796145,0.003429047,0.0006683398,0.00168468,0.001012776,0.0004149574,0.3736508],"category_scores_gemma":[0.007979505,0.0003367095,0.001558935,0.005603966,0.0003769207,0.0008396407,0.000784124,0.0006236322,0.05463911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003230511,"about_ca_system_score_gemma":0.004677101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5542573,"about_ca_topic_score_gemma":0.651461,"domain_scores_codex":[0.9990984,0.0001114377,0.00005954349,0.0001859451,0.0003432028,0.0002014505],"domain_scores_gemma":[0.9947028,0.001137988,0.0009477981,0.000366251,0.00239852,0.000446687],"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":[0.0002496644,0.00004076417,0.04860082,0.0004598048,0.0001016814,0.00006284579,0.0001756401,0.001168966,0.0002050691,0.001622867,0.9229959,0.02431604],"study_design_scores_gemma":[0.0002937937,0.00009922894,0.5884169,0.0006920366,0.0001288841,0.0003908626,0.001221694,0.00286223,0.0005593679,0.001018161,0.4042419,0.00007487565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01148285,0.000236262,0.0009132919,0.0008012085,0.0001830957,0.0002057955,0.9308665,0.001654441,0.05365657],"genre_scores_gemma":[0.146219,0.0006502768,0.006341485,0.001135249,0.0001619195,0.0005658948,0.674193,0.002188241,0.168545],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6263492,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3379419253645394,"score_gpt":0.4197163459747449,"score_spread":0.08177442061020557,"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."}}