{"id":"W4211135352","doi":"10.36227/techrxiv.19137518.v1","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":0,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000835945,0.0009931671,0.0007684654,0.00142502,0.0002244247,0.001011418,0.001235057,0.0009879072,0.005350846],"category_scores_gemma":[0.003087441,0.0006619955,0.0009202707,0.001785028,0.0005647399,0.001201242,0.001227367,0.001580245,0.002121547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048056,"about_ca_system_score_gemma":0.001199285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006632317,"about_ca_topic_score_gemma":0.008270835,"domain_scores_codex":[0.9995597,0.00009172097,0.00002795969,0.00009502772,0.0001894132,0.00003612694],"domain_scores_gemma":[0.9993432,0.0002810454,0.00009719276,0.0001070419,0.0001436875,0.00002774895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001947035,0.00006184258,0.001372453,0.0007881218,0.0002634426,0.0002462085,0.00008282123,0.3187989,0.02031466,0.02811313,0.02956164,0.600202],"study_design_scores_gemma":[0.00001287737,0.0000217318,0.0005793396,0.00004991094,0.00002553552,0.0001126527,0.00001319661,0.9637999,0.00412513,0.02190098,0.009338866,0.0000198472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004358542,0.003685743,0.9852722,0.000852401,0.0001126345,0.00005666451,0.0007387126,0.002725091,0.002198062],"genre_scores_gemma":[0.2378924,0.0114344,0.7345607,0.0007290781,0.0003959837,0.0003988474,0.004433617,0.0008100693,0.009345019],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006632317,"threshold_uncertainty_score":0.01790041,"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."}}