{"id":"W4393639090","doi":"10.5281/zenodo.5656776","title":"Indian Brain Segmentation Dataset(IBSD)","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Segmentation; Artificial intelligence; Pattern recognition (psychology); Geography; Computer science; Cartography","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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006454753,0.0002846897,0.0002325597,0.0004509162,0.002610867,0.001687747,0.001559871,0.0002037561,0.03735742],"category_scores_gemma":[0.0033091,0.0003254048,0.00007745518,0.001040338,0.0002192963,0.0003682044,0.001129367,0.0007484267,0.02361271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002751312,"about_ca_system_score_gemma":0.00001476845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002324065,"about_ca_topic_score_gemma":0.00000283787,"domain_scores_codex":[0.9962265,0.001164603,0.0004230693,0.001016487,0.0007299121,0.0004394],"domain_scores_gemma":[0.9979146,0.0001053536,0.0003295594,0.001162001,0.0002378575,0.0002506761],"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":[0.00002565413,0.0001422169,2.087816e-8,0.0001076667,0.00001224158,0.00007007641,0.0001132844,0.000004827407,0.01974607,0.000100519,0.9607024,0.01897508],"study_design_scores_gemma":[0.0004088024,0.0001168118,0.00001298318,0.00004208974,0.00002025743,0.0003977368,0.000244039,0.00003088062,0.007218759,0.00003759152,0.9911506,0.000319484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001257195,0.00002458068,0.0002464863,0.001525304,0.0003921056,0.0005350932,0.9929435,0.000475806,0.003731359],"genre_scores_gemma":[0.0008013375,0.0001934601,0.00003152475,0.002112051,0.0002719598,2.031734e-7,0.995066,0.000890736,0.0006327606],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03044822,"threshold_uncertainty_score":0.9999198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06172128640475189,"score_gpt":0.2886560715500109,"score_spread":0.2269347851452591,"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."}}