{"id":"W4211047491","doi":"10.36227/techrxiv.19137518","title":"Sparse Convolutional Neural Networks for Medical Image Analysis","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Inference; Voxel; Pattern recognition (psychology); Skull; Computer vision","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006019768,0.0002807138,0.0006587351,0.0003202706,0.0000971455,0.00007202201,0.0005072301,0.0002503821,0.02011062],"category_scores_gemma":[0.0001799129,0.0002640813,0.000893349,0.0004990947,0.0000963571,0.00003417602,0.0004159948,0.001123724,0.000009290546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020028,"about_ca_system_score_gemma":0.00006153406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001024128,"about_ca_topic_score_gemma":0.0000315506,"domain_scores_codex":[0.9978931,0.0000579867,0.0004974652,0.0004340571,0.0007148809,0.0004025305],"domain_scores_gemma":[0.9988443,0.0002519556,0.00005586646,0.0004334913,0.00006262308,0.0003517107],"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":[0.000002332717,0.00002674531,0.001193762,0.00008801627,0.002534437,0.00002335435,0.00001506147,0.9509133,0.000002793724,0.0002052364,0.04223509,0.002759892],"study_design_scores_gemma":[0.0001823026,0.000003886195,0.0003630716,0.000009135967,0.001546985,0.000002078285,0.00002433341,0.9915531,0.000001753858,0.0002137954,0.005816522,0.0002830411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003806326,0.0009448758,0.9883773,0.001104973,0.001139986,0.0001664277,0.0001256481,0.0006016268,0.003732791],"genre_scores_gemma":[0.9803573,0.0003231935,0.009922611,0.0008864535,0.001362041,0.0004206124,0.004030355,0.00008828549,0.002609076],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9784547,"threshold_uncertainty_score":0.9999812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01394205101834982,"score_gpt":0.2658912126915114,"score_spread":0.2519491616731616,"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."}}