{"id":"W1707563711","doi":"10.2196/ijmr.3495","title":"A Virtual Microscope for Academic Medical Education: The Pate Project","year":2015,"lang":"en","type":"article","venue":"Interactive Journal of Medical Research","topic":"AI in cancer detection","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Virtual microscopy; Telepathology; Set (abstract data type); Medical education; Scope (computer science); Sample (material); Psychology; Computer science; Mathematics education; Medicine; Pathology; Health care; Telemedicine; Political science; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00495715,0.0006200381,0.0002585447,0.000954779,0.0007882753,0.002146929,0.001354753,0.001209924,0.02732605],"category_scores_gemma":[0.007829605,0.0003254895,0.0006162279,0.0006111076,0.0008449639,0.002625096,0.005767666,0.001474048,0.007304223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005975959,"about_ca_system_score_gemma":0.001939994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004078485,"about_ca_topic_score_gemma":0.0009395615,"domain_scores_codex":[0.9974368,0.001169053,0.0000905967,0.0002882383,0.000798344,0.0002170195],"domain_scores_gemma":[0.9929205,0.002183876,0.0003269428,0.0007655644,0.0006946611,0.003108444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003593547,0.001214583,0.007325466,0.0005880979,0.00003573294,0.0006714172,0.001792022,0.001953678,0.01434214,0.005732337,0.2414161,0.7245691],"study_design_scores_gemma":[0.0002393209,0.00155878,0.02127025,0.0005777095,0.00004293334,0.00526958,0.002106935,0.01111503,0.01264832,0.01007619,0.9349823,0.0001127191],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2352801,0.009137126,0.5103169,0.03680695,0.004930141,0.002577281,0.007023244,0.04314065,0.1507877],"genre_scores_gemma":[0.3027403,0.006978165,0.5841535,0.004787569,0.00114345,0.001936886,0.005763208,0.003124015,0.08937281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02732605,"threshold_uncertainty_score":0.09141475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1669686288690548,"score_gpt":0.5383615392905717,"score_spread":0.371392910421517,"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."}}