{"id":"W4401025043","doi":"10.24963/ijcai.2024/475","title":"Adaptive Deep Learning from Crowds","year":2024,"lang":"en","type":"article","venue":"","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Institute for Information and Communications Technology Promotion; Samsung; Ministry of Science and ICT, South Korea; National Research Foundation of Korea; National Research Foundation","keywords":"Reinforcement learning; Pareto principle; Computer science; Inverse; Artificial intelligence; Mathematical optimization; Machine learning; Mathematics","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":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001446406,0.0001199434,0.0002358418,0.0002842245,0.0001623969,0.001368175,0.0004892103,0.00005838332,0.01379067],"category_scores_gemma":[0.001224458,0.00007412804,0.0001704395,0.000859142,0.00003413259,0.000329788,0.000235549,0.0002080328,0.01065028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002868751,"about_ca_system_score_gemma":0.00003486438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002768059,"about_ca_topic_score_gemma":0.0001755099,"domain_scores_codex":[0.9971184,0.0001727893,0.0005548481,0.0006139723,0.001340361,0.0001996446],"domain_scores_gemma":[0.9950384,0.004236962,0.00006111964,0.0004031233,0.00015674,0.0001035804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002686007,0.00001155171,0.002572274,0.000001540345,0.00003941619,0.0001580758,0.001669878,0.002364575,0.0005707119,0.1675022,0.07037873,0.7547042],"study_design_scores_gemma":[0.00007308157,0.00003715322,0.005136541,0.00003356514,0.000004364113,0.000008980316,0.001963241,0.389127,0.00003967142,0.2173861,0.3860516,0.000138768],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03103765,0.005564568,0.7282387,0.0002073094,0.001704181,0.00009268726,0.000003692384,0.000328079,0.2328231],"genre_scores_gemma":[0.9540322,0.000001936821,0.003594524,0.00009796713,0.0002997107,0.00000406494,4.735208e-7,0.00001214169,0.041957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9229946,"threshold_uncertainty_score":0.9996685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2111877717524739,"score_gpt":0.4070293335310882,"score_spread":0.1958415617786143,"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."}}