{"id":"W4407910063","doi":"10.2139/ssrn.5153814","title":"Tdri: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Adaptation (eye); Phase (matter); Image (mathematics); Computer science; Human–computer interaction; Artificial intelligence; Psychology; Chemistry","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001446014,0.0002660943,0.0002678215,0.0002769229,0.000382732,0.0004372366,0.0006604149,0.0001179969,0.000003767448],"category_scores_gemma":[0.0001586185,0.000264771,0.0001251226,0.0001250838,0.00003257387,0.0002895741,0.0003211071,0.002458039,0.000005861684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001100243,"about_ca_system_score_gemma":0.002331589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004909318,"about_ca_topic_score_gemma":0.0008353994,"domain_scores_codex":[0.9976077,0.0001954843,0.0004451722,0.0005912047,0.0002286771,0.0009317823],"domain_scores_gemma":[0.9985148,0.000169234,0.0005095898,0.0004322711,0.0002955165,0.00007861927],"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":[0.0001019384,0.0003456068,0.00008318403,0.00006805329,0.0004167148,0.000002011367,0.002119089,0.01368459,0.004821494,0.5078784,0.0006429463,0.469836],"study_design_scores_gemma":[0.001963031,0.0002994989,0.0001248421,0.00005221447,0.00006643937,0.00005099995,0.000119245,0.8200524,0.0004378773,0.1750637,0.001479777,0.0002899896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0220668,0.0004921266,0.9717187,0.004119586,0.0004017335,0.0007445585,0.00003836294,0.0000804322,0.0003376949],"genre_scores_gemma":[0.8891913,0.000798219,0.1077003,0.0002515466,0.0007191075,0.000418079,0.000318491,0.00002314946,0.0005798803],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8671245,"threshold_uncertainty_score":0.9999804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02233089557443285,"score_gpt":0.3583350478680937,"score_spread":0.3360041522936608,"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."}}