{"id":"W4414018262","doi":"10.3390/a18090564","title":"The Generative Adversarial Approach: A Cautionary Tale of Finite Samples","year":2025,"lang":"en","type":"article","venue":"Algorithms","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Adversarial system; Generative grammar; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01895601,0.001222749,0.001638738,0.001230281,0.001577635,0.004050395,0.004077282,0.005249742,0.003458059],"category_scores_gemma":[0.06318335,0.0006528368,0.0009116976,0.0007559356,0.01645368,0.009160503,0.00399423,0.02466635,0.00139134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508972,"about_ca_system_score_gemma":0.001125089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490303,"about_ca_topic_score_gemma":0.002125567,"domain_scores_codex":[0.992202,0.004967801,0.0002683258,0.000909557,0.001534615,0.0001176167],"domain_scores_gemma":[0.9491598,0.04340253,0.0009471165,0.00431226,0.001741271,0.0004369827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008195533,0.00002708224,0.0006381491,0.0002995484,0.0001035367,0.000283113,0.0006076774,0.01424571,0.0004782302,0.9188635,0.03065468,0.03371678],"study_design_scores_gemma":[0.0000280128,0.00003366647,0.0001435614,0.0002746314,0.00001611046,0.0002359258,0.00009935143,0.02829997,0.0004961138,0.938211,0.0321189,0.00004295487],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003385031,0.01136463,0.8084941,0.1553336,0.003379953,0.00008078349,0.0001760638,0.0004887999,0.01729694],"genre_scores_gemma":[0.3073618,0.0208798,0.5347607,0.09633189,0.01455558,0.001009715,0.0002004132,0.001404194,0.02349596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01895601,"threshold_uncertainty_score":0.1002502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01832867434264071,"score_gpt":0.2573769284330431,"score_spread":0.2390482540904024,"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."}}