{"id":"W2913950239","doi":"10.7717/peerj.6333","title":"X-ray vision: the accuracy and repeatability of a technology that allows clinicians to see spinal X-rays superimposed on a person's back","year":2019,"lang":"en","type":"article","venue":"PeerJ","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Repeatability; Medical physics; Computer science; Artificial intelligence; Medicine; Optometry; Computer vision; Physical medicine and rehabilitation; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003946091,0.0001292204,0.0003036564,0.00009634721,0.0000352492,0.00002173368,0.0002241517,0.00008243095,0.0002733493],"category_scores_gemma":[0.0003389023,0.00008720667,0.00009217906,0.0002487712,0.00008974226,0.00005253517,0.00004856552,0.00025113,0.0001924073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001942434,"about_ca_system_score_gemma":0.00001230318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002713894,"about_ca_topic_score_gemma":0.00000719917,"domain_scores_codex":[0.9991097,0.00003228441,0.0001835025,0.0002537893,0.0002143198,0.0002064245],"domain_scores_gemma":[0.9991249,0.0001753979,0.0000291889,0.000551728,0.00003553133,0.00008323789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002540191,0.0005310489,0.4722415,0.001318579,0.0007535021,0.00005680686,0.007292437,0.0102611,0.1887246,0.0006918461,0.0148259,0.3030486],"study_design_scores_gemma":[0.004156463,0.00264345,0.5253299,0.001373465,0.0004940493,0.00005785415,0.01454314,0.2010499,0.01487935,0.0004035382,0.2333237,0.001745113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903995,0.0002055625,0.0003840112,0.007067976,0.0001283204,0.0001819544,0.000008953324,0.0001004496,0.001523313],"genre_scores_gemma":[0.9985957,0.00003444554,0.0007293408,0.0002967303,0.00003986733,0.000007783069,0.000002590116,0.00001492112,0.0002786376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3013035,"threshold_uncertainty_score":0.3556184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941104835222616,"score_gpt":0.2773007643369818,"score_spread":0.2578897159847556,"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."}}