{"id":"W7126405082","doi":"10.21428/594757db.b3a27711","title":"On Neural Process Pooling Operator Choice and PosteriorCalibration","year":2024,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pooling; Inference; Conditioning; Artificial neural network; Process (computing); Predictive inference; Term (time)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001087149,0.00008914473,0.00006753144,0.00007542871,0.00009843482,0.0006535713,0.0002357659,0.00003320866,0.00002694594],"category_scores_gemma":[0.000090928,0.00007055814,0.00001510378,0.0002398512,0.0000143405,0.001034533,0.0001233213,0.0001652579,0.00001781318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001344475,"about_ca_system_score_gemma":0.00003134471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001204915,"about_ca_topic_score_gemma":0.000002252172,"domain_scores_codex":[0.9992853,0.00003380429,0.00009987131,0.0003111798,0.0001424021,0.000127431],"domain_scores_gemma":[0.9996346,0.0001417993,0.00001356867,0.0001421098,0.00001974727,0.00004814196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001808962,0.00004396939,0.003956006,0.0002572304,0.0000411041,0.0001126783,0.004459771,0.133886,0.00397492,0.5903494,0.0006261111,0.2622747],"study_design_scores_gemma":[0.00007651519,0.00005142383,0.0008863367,0.00003424528,0.000002285484,0.00001543328,0.00001276817,0.9971423,0.000423639,0.001032639,0.0002220317,0.0001003939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3498999,0.0001078196,0.6428105,0.003551338,0.0006112355,0.0001049382,3.204997e-7,0.0005546796,0.002359378],"genre_scores_gemma":[0.9929566,0.000001128395,0.005839084,0.0007711198,0.0001242516,0.000004508695,8.752092e-7,0.000009066537,0.0002933227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8632563,"threshold_uncertainty_score":0.6302403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00951831460353636,"score_gpt":0.2883884421740188,"score_spread":0.2788701275704825,"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."}}