{"id":"W6902175400","doi":"10.6084/m9.figshare.26589999","title":"Additional file 1 of Biased data, biased AI: deep networks predict the acquisition site of TCGA images","year":2024,"lang":"en","type":"article","venue":"Open MIND","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Ontario Tech University; Brock University; William Osler Health System; Laurentian University; McMaster University; University Health Network","funders":"","keywords":"Table (database); Deep learning; Source code; Deep neural networks; File format","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001703211,0.001686935,0.001206466,0.001902377,0.0008640918,0.001941311,0.002297422,0.001717932,0.7553644],"category_scores_gemma":[0.03246241,0.000655462,0.0009785957,0.002549752,0.0003821642,0.001773772,0.001313642,0.001559838,0.179882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057079,"about_ca_system_score_gemma":0.001690223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005660461,"about_ca_topic_score_gemma":0.01348279,"domain_scores_codex":[0.9991799,0.0001173875,0.0001019392,0.0002692059,0.0002228354,0.0001086452],"domain_scores_gemma":[0.9817703,0.01328896,0.0007629269,0.001784036,0.001973809,0.0004199395],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000314443,0.0001024691,0.00252373,0.001429214,0.00006185906,0.00005980675,0.00002799997,0.0007026131,0.0002591895,0.0004190039,0.985276,0.008823713],"study_design_scores_gemma":[0.007338701,0.0006342286,0.03408457,0.00279827,0.0003873473,0.001186756,0.0004282719,0.01314601,0.00648057,0.02207171,0.9111601,0.0002834912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0002592072,0.00001989982,0.0004760252,0.00006804806,0.00003369779,0.00003725082,0.997898,0.0008542973,0.0003535352],"genre_scores_gemma":[0.005939159,0.00006719232,0.004744707,0.0003304163,0.00008334529,0.0009241849,0.983026,0.001421146,0.003463792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9982968,"threshold_uncertainty_score":0.3489431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03181115205597294,"score_gpt":0.2887079528766788,"score_spread":0.2568968008207058,"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."}}