{"id":"W7105599236","doi":"10.1109/access.2025.3632686","title":"Comparative Evaluation of Reasoning and Inference in LLM-Based and Diffusion-Based Approaches","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inference; Generative grammar; Opportunistic reasoning; Model-based reasoning; Qualitative reasoning; Reasoning system; Process (computing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01764692,0.0008496006,0.001138633,0.002458218,0.0009621703,0.002822185,0.003677716,0.002051512,0.003658026],"category_scores_gemma":[0.05320642,0.0004382924,0.001412235,0.001861764,0.001548933,0.007722848,0.002794928,0.002833206,0.0006784394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005284268,"about_ca_system_score_gemma":0.003593925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159486,"about_ca_topic_score_gemma":0.01185105,"domain_scores_codex":[0.9909782,0.004712733,0.000660356,0.001251976,0.002092998,0.0003036983],"domain_scores_gemma":[0.9593,0.03283786,0.0009270507,0.002609623,0.003188252,0.001137031],"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":[0.002471065,0.001622619,0.01630429,0.00204256,0.0008707023,0.0001619667,0.002664189,0.2254497,0.003803378,0.0616544,0.004169769,0.6787854],"study_design_scores_gemma":[0.0002189864,0.000435449,0.003850124,0.0001413463,0.0002710317,0.00009582163,0.0004985433,0.9596789,0.003023103,0.02747754,0.004237597,0.00007151546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3472167,0.009275629,0.5972983,0.004632932,0.0005445821,0.001046205,0.0006422436,0.004840502,0.03450282],"genre_scores_gemma":[0.785381,0.001686094,0.2085113,0.0004739875,0.00009983573,0.0002748069,0.0007233311,0.0002332581,0.002616407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01764692,"threshold_uncertainty_score":0.09332699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1526966410294123,"score_gpt":0.4302979386398004,"score_spread":0.2776012976103881,"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."}}