{"id":"W4393493527","doi":"10.5281/zenodo.5189179","title":"MICCAI 2016 challenge dataset demographics data","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Demographics; Computer science; Geography; Data science; Demography","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":[0.001433598,0.003219624,0.002091105,0.002755395,0.001257255,0.001941578,0.003414255,0.003097642,0.03719212],"category_scores_gemma":[0.006053074,0.0005204617,0.001569819,0.003597284,0.000512411,0.00165841,0.002235076,0.002389153,0.08838107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001722878,"about_ca_system_score_gemma":0.002687285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02479474,"about_ca_topic_score_gemma":0.05449091,"domain_scores_codex":[0.9985677,0.0002847998,0.0001269605,0.0004340666,0.0003583969,0.0002279361],"domain_scores_gemma":[0.9982316,0.0003165422,0.0001056726,0.0004241668,0.0007127676,0.0002092767],"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":[0.0000885647,0.00004084439,0.0004948156,0.0001909156,0.0000230342,0.00002829856,0.00001128835,0.000329614,0.0001435666,0.0002159978,0.9944379,0.00399526],"study_design_scores_gemma":[0.0003480754,0.00008015509,0.0068383,0.0002339284,0.00006676534,0.0003639709,0.0001411556,0.004377217,0.001175672,0.003045605,0.9832513,0.00007786677],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001134542,0.0003304126,0.0005086413,0.0003330168,0.0001794681,0.00006201128,0.9929374,0.002319427,0.002195139],"genre_scores_gemma":[0.001031847,0.0000765208,0.0006332376,0.0001155552,0.00002891325,0.0001092287,0.9966424,0.000135061,0.001227255],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03719212,"threshold_uncertainty_score":0.12442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07232141956291117,"score_gpt":0.28816561634031,"score_spread":0.2158441967773988,"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."}}