{"id":"W6969710977","doi":"10.5683/sp3/gzndgw","title":"Fully connected networks - 15000 synthesis samples","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"COVID-19 Impact on Reproduction","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Artificial neural network; Latency (audio); Hyperparameter; Synthetic data; Regression; Pattern recognition (psychology)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000429193,0.0004945194,0.0008381834,0.0004503649,0.00007818887,0.0001092083,0.000255192,0.000611218,0.001173386],"category_scores_gemma":[0.003555416,0.0004236651,0.0002926623,0.0004807616,0.0001156204,0.00005955346,0.0001336656,0.0007857794,0.0004263705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003636604,"about_ca_system_score_gemma":0.0005106127,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04602125,"about_ca_topic_score_gemma":0.006774561,"domain_scores_codex":[0.9974672,0.0001065011,0.0005087897,0.0009091342,0.0005240337,0.0004843638],"domain_scores_gemma":[0.9968194,0.0005748952,0.000193341,0.001955832,0.0001633516,0.0002931283],"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":[0.0002005052,0.00009571525,0.00002873204,0.0008664895,0.0004194809,0.0003152334,0.0000177582,0.00002217599,0.00001655716,0.00001680439,0.9944108,0.003589751],"study_design_scores_gemma":[0.0002392144,0.0001348599,0.001383311,0.0007780371,0.001874027,0.0002368734,0.00002600858,0.00007256786,0.00005723148,0.00007276276,0.9947424,0.0003826977],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000020038,0.001345766,0.00004482805,0.005388418,0.0007620843,0.0006671487,0.9910663,0.0003895013,0.0003158826],"genre_scores_gemma":[0.0001047743,0.001331459,0.00007670829,0.001736068,0.003252365,0.0001378747,0.9930479,0.00009248084,0.0002203718],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03924669,"threshold_uncertainty_score":0.9998215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03237377540616761,"score_gpt":0.3163277850134695,"score_spread":0.2839540096073019,"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."}}