{"id":"W4385841175","doi":"10.1259/bjro.20230008","title":"The effect of spatial resolution on deep learning classification of lung cancer histopathology","year":2023,"lang":"en","type":"article","venue":"BJR|Open","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Okanagan University College; University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"BC Cancer Foundation","keywords":"Histopathology; Lung cancer; Adenocarcinoma; Pathology; Convolutional neural network; Cancer; Medicine; Artificial intelligence; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002206625,0.0007313674,0.0002895796,0.0005386953,0.0001927826,0.0007385587,0.0005192836,0.0007976586,0.0009816693],"category_scores_gemma":[0.01138353,0.000300889,0.0004475923,0.0004115948,0.0004701584,0.001162331,0.0009412953,0.0007923963,0.0002681561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006458948,"about_ca_system_score_gemma":0.0004578156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003552239,"about_ca_topic_score_gemma":0.002894749,"domain_scores_codex":[0.9993692,0.0001936465,0.00005131962,0.0001327005,0.0001757292,0.00007739933],"domain_scores_gemma":[0.9953992,0.003296881,0.000356488,0.0002692184,0.0005573473,0.0001208939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001745051,0.0003485698,0.05295357,0.0004732558,0.0003854054,0.0003493189,0.0002037332,0.5306914,0.1217266,0.001800761,0.001688728,0.2876335],"study_design_scores_gemma":[0.00003998334,0.0004452884,0.02126807,0.00008476995,0.0001450625,0.0002164635,0.00006780425,0.9072434,0.06739898,0.001973493,0.001079745,0.00003687026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9225398,0.002123732,0.07032948,0.0007977175,0.0000766553,0.00003532833,0.0003365833,0.0009206315,0.002840143],"genre_scores_gemma":[0.9789368,0.0003742915,0.01966157,0.0001274213,0.00001751124,0.00001193332,0.000255297,0.00004166647,0.0005734335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003552239,"threshold_uncertainty_score":0.01166987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02625992649610099,"score_gpt":0.3295964279005444,"score_spread":0.3033365014044435,"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."}}