{"id":"W2968456576","doi":"10.4103/jpi.jpi_31_19","title":"2020 Vision of Digital Pathology in Action","year":2019,"lang":"en","type":"editorial","venue":"Journal of Pathology Informatics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network","funders":"","keywords":"Digital pathology; Computer science; Action (physics); Pathology; Artificial intelligence; Medicine","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001248517,0.0002118394,0.001183391,0.0005877475,0.00001719176,0.0000231985,0.0002327302,0.0009373933,0.00002768483],"category_scores_gemma":[0.004756301,0.000163721,0.0002440537,0.0001681949,0.000168095,0.0003349573,0.00008768212,0.003086713,0.00002316367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001451667,"about_ca_system_score_gemma":0.0006018468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001090434,"about_ca_topic_score_gemma":5.025551e-7,"domain_scores_codex":[0.9970205,0.00007837094,0.001895379,0.00008625637,0.0006786014,0.0002409379],"domain_scores_gemma":[0.9962218,0.0006329797,0.002325566,0.0002482158,0.0004600176,0.0001114158],"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":[0.0004809275,0.000238404,0.003848913,0.001424931,0.0001017677,0.002468232,0.00180638,0.000259356,0.0004354659,0.00001310481,0.963683,0.02523953],"study_design_scores_gemma":[0.009163762,0.005463332,0.002762598,0.003244814,0.0005310118,0.01254009,0.001210143,0.004744287,0.00007287986,0.0003939009,0.9594535,0.0004197148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.2473193,0.0004154947,0.002646314,0.0007464598,0.7466198,0.0002681474,0.00005067119,0.00001326141,0.001920481],"genre_scores_gemma":[0.09848572,0.008994028,0.02000507,0.0007968976,0.8691351,0.00000567199,0.0007590717,0.0001771548,0.001641248],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1488336,"threshold_uncertainty_score":0.9992132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00748709512679094,"score_gpt":0.3229791782215725,"score_spread":0.3154920830947816,"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."}}