{"id":"W4393512592","doi":"10.5281/zenodo.3769289","title":"Example DWI Dataset including minimally preprocessed and co-registered data","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Data mining","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","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00134262,0.0002841925,0.0002924627,0.0002527398,0.001900285,0.003171739,0.008038645,0.0001399322,0.001146236],"category_scores_gemma":[0.002191337,0.0003030758,0.00002290284,0.00057256,0.0001638025,0.0009976516,0.01330993,0.0006560674,0.007452418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006527204,"about_ca_system_score_gemma":0.00001941991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001970804,"about_ca_topic_score_gemma":0.00000332482,"domain_scores_codex":[0.9964254,0.0005576712,0.0004238928,0.001630404,0.0005890509,0.0003736207],"domain_scores_gemma":[0.9952539,0.00008518515,0.0004033366,0.003745929,0.0002215044,0.0002901374],"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":[0.00002453243,0.00006051098,4.430987e-7,0.0002899019,0.00003398805,0.00002036702,0.0001480852,0.00000174013,0.0001306148,0.0001882988,0.9688408,0.03026075],"study_design_scores_gemma":[0.0003478801,0.0001428054,0.00006760239,0.00005446922,0.00002654619,0.00009952127,0.0000296558,0.003261641,0.00001051712,0.00002662769,0.9956213,0.0003114991],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007258524,0.00009848006,0.01358363,0.001328333,0.00007612983,0.0003574017,0.9824572,0.0005781025,0.00151351],"genre_scores_gemma":[0.0002131333,0.0003083765,0.001660652,0.000388207,0.0001832526,7.105024e-8,0.9967369,0.0004269902,0.00008244233],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02994926,"threshold_uncertainty_score":0.9999421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1917081272317144,"score_gpt":0.33734286289932,"score_spread":0.1456347356676056,"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."}}