{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002034159,0.0003981175,0.0003420379,0.0002066531,0.002350818,0.0006661487,0.00476033,0.000280395,0.11924],"category_scores_gemma":[0.001180658,0.0004414639,0.00005950406,0.0006600098,0.0005686435,0.000628112,0.01580242,0.001147725,0.0744907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003608802,"about_ca_system_score_gemma":0.00001019895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000264956,"about_ca_topic_score_gemma":0.00002367814,"domain_scores_codex":[0.9947562,0.001041376,0.00049393,0.001899,0.0009984652,0.0008110379],"domain_scores_gemma":[0.9951353,0.00007589823,0.000291942,0.003975536,0.00005925873,0.0004620719],"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":[0.00001304275,0.0002471389,0.000001255393,0.0001022174,0.00004934563,0.0001063032,0.00004596065,0.00001085634,0.00007519581,0.000005703509,0.9730615,0.02628146],"study_design_scores_gemma":[0.0003307872,0.0001021787,0.0001381145,0.00008354007,0.00006415196,0.00009695637,0.00009302516,0.00008646282,0.000006844587,0.00002192048,0.9985259,0.0004501473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005191929,0.0002645091,0.0002646564,0.0009347382,0.0001545728,0.0006579691,0.9904413,0.0001998302,0.007030495],"genre_scores_gemma":[0.00009062196,0.006010907,0.000178433,0.0008380104,0.0002218499,1.071741e-7,0.991284,0.001185576,0.0001904963],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04474927,"threshold_uncertainty_score":0.9998037,"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."}}