{"id":"W4415142852","doi":"","title":"COUNTLOOP: Iterative Agent Guided High Instance Image Generation","year":2025,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Simon Fraser University","funders":"","keywords":"Masking (illustration); Object (grammar); Image (mathematics); Quality (philosophy); Iterative refinement; Iterative method; Image quality","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"],"consensus_categories":[],"category_scores_codex":[0.001724225,0.000441572,0.0004023941,0.0002092034,0.0003138721,0.0004606329,0.001039898,0.0003436247,0.0001164876],"category_scores_gemma":[0.0004393005,0.0005295863,0.0001582069,0.0003929712,0.0001333621,0.0001699655,0.0006906046,0.0007085216,0.00007415799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003985278,"about_ca_system_score_gemma":0.0002487007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008611684,"about_ca_topic_score_gemma":0.001737813,"domain_scores_codex":[0.996686,0.001111268,0.0007208883,0.0007483661,0.0003888385,0.0003446636],"domain_scores_gemma":[0.994547,0.0004066089,0.0002524406,0.002225301,0.002437687,0.0001309646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001267555,0.001025483,0.0003547987,0.001495975,0.0007009382,0.00001263316,0.02473419,0.3827087,0.06887987,0.3796195,0.07717396,0.06328131],"study_design_scores_gemma":[0.000391434,1.892449e-7,0.0003063833,0.001160001,0.00007245722,0.00000238182,0.00002507127,0.8819644,0.09457806,0.004995982,0.01586574,0.0006378987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0419409,0.0009027009,0.9112289,0.003004384,0.0006436965,0.0008117259,0.0004345675,0.0008097227,0.0402234],"genre_scores_gemma":[0.609415,0.001481136,0.3762877,0.0001838798,0.0001179451,0.0007769146,0.003150708,0.00009559278,0.008491163],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5674741,"threshold_uncertainty_score":0.9997156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726632679058626,"score_gpt":0.235451988384202,"score_spread":0.2181856615936157,"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."}}