{"id":"W7092458970","doi":"10.1080/10618600.2025.2574532","title":"Reproducing Kernel-Based Semiparametric Functional Smoothed Score Estimation with Binary Responses","year":2025,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Alberta Machine Intelligence Institute","keywords":"Binary data; Binary number; Estimation; Covariate; Functional data analysis; Semiparametric model; Estimation theory; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004323836,0.0001050085,0.0001805751,0.000606771,0.0001335735,0.0000396488,0.0000480031,0.00006797227,0.0001516529],"category_scores_gemma":[0.0003530949,0.00008133358,0.00004601718,0.0005991205,0.0001472525,0.00006552922,0.000009068292,0.0002421695,0.000004319863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002311215,"about_ca_system_score_gemma":0.0001632778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005928465,"about_ca_topic_score_gemma":0.000001928798,"domain_scores_codex":[0.9988424,0.000157997,0.0004158942,0.0001775258,0.0002984863,0.0001076677],"domain_scores_gemma":[0.9977816,0.001246515,0.0002825833,0.00006986011,0.0005414889,0.00007799859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.01111654,0.002047313,0.08460428,0.000327638,0.0009519584,0.0003799831,0.0004348746,0.1882305,0.000151069,0.3861678,0.04014509,0.2854429],"study_design_scores_gemma":[0.002124398,0.0006896845,0.8087396,0.0001706036,0.0001213528,0.0001610502,0.00005899033,0.03231191,0.00001777468,0.1551783,0.0003030579,0.0001232704],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2726678,0.000199576,0.7252274,0.001131015,0.000324766,0.00008051725,0.00004222639,0.00001352016,0.0003131424],"genre_scores_gemma":[0.931638,0.00000894851,0.06738128,0.0005891354,0.00007377296,0.000003644665,0.00006238447,0.000007391609,0.0002354276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7241353,"threshold_uncertainty_score":0.3316687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0279213443795776,"score_gpt":0.3138558903931978,"score_spread":0.2859345460136202,"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."}}