{"id":"W4366606355","doi":"10.1212/wnl.0000000000207102","title":"Section 1: Images by Subspecialty","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Section (typography); Subspecialty; Medicine; Medical physics; Artificial intelligence; Computer science; Pathology","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":[0.001432474,0.001193794,0.0006811731,0.004507423,0.001134099,0.002219211,0.0009744169,0.001909206,0.1973054],"category_scores_gemma":[0.009482398,0.0008111154,0.0005802853,0.002800203,0.000760088,0.002128741,0.00151535,0.001548594,0.08096076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029522,"about_ca_system_score_gemma":0.002377369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001777735,"about_ca_topic_score_gemma":0.004658122,"domain_scores_codex":[0.9988773,0.0001994044,0.0001686648,0.0001821662,0.0004456602,0.0001268093],"domain_scores_gemma":[0.9925458,0.001957652,0.0005720155,0.000476326,0.00350896,0.0009393035],"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":[0.0001015095,0.0001013241,0.001239294,0.001020283,0.00002148881,0.0003600736,0.00004258312,0.0003180793,0.004049218,0.004265899,0.7793165,0.2091637],"study_design_scores_gemma":[0.00001589954,0.0001771779,0.005345798,0.0008429218,0.00002418739,0.00215275,0.00007032784,0.0007405392,0.004710775,0.006026812,0.9798682,0.00002460686],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01847902,0.06882524,0.1166964,0.04433745,0.2473478,0.003117678,0.009623183,0.005125497,0.4864478],"genre_scores_gemma":[0.03666143,0.06151228,0.04951526,0.01747224,0.09640958,0.000848987,0.01185275,0.003310985,0.7224165],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1973054,"threshold_uncertainty_score":0.6600523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0136515673071758,"score_gpt":0.2762422479830521,"score_spread":0.2625906806758763,"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."}}