{"id":"W4394055437","doi":"10.5281/zenodo.4733385","title":"DJIN model of aging synthetic dataset","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science","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":[0.001620179,0.001379152,0.0007539439,0.00120871,0.0005331457,0.0008827266,0.002781759,0.001737949,0.01809675],"category_scores_gemma":[0.005430396,0.0004250144,0.001415389,0.001386595,0.0003637827,0.0005659873,0.0009606174,0.001828151,0.01703018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378386,"about_ca_system_score_gemma":0.001495517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02168922,"about_ca_topic_score_gemma":0.04185983,"domain_scores_codex":[0.999451,0.000198901,0.00004415496,0.0001489312,0.00007915292,0.00007785972],"domain_scores_gemma":[0.9989554,0.0003504538,0.00007272331,0.0002292391,0.0002767273,0.0001153582],"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":[0.0002964494,0.0002450474,0.006634259,0.0004483643,0.0001347943,0.0001442033,0.00004603088,0.01613712,0.0002201695,0.00177115,0.9628399,0.01108249],"study_design_scores_gemma":[0.001366869,0.0003682033,0.02873064,0.0004993026,0.0002157712,0.0007312773,0.0002171449,0.1054542,0.001524964,0.01217388,0.848582,0.0001357648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01281711,0.0007326298,0.003273077,0.0009197434,0.0003161537,0.0002074205,0.9766248,0.001875795,0.003233325],"genre_scores_gemma":[0.01742058,0.000249747,0.004515699,0.0004358894,0.00005698463,0.000501863,0.973009,0.0001641601,0.003646044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02168922,"threshold_uncertainty_score":0.06053966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2794555128427829,"score_gpt":0.356692318225389,"score_spread":0.07723680538260613,"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."}}