{"id":"W4400315661","doi":"10.1109/isivc61350.2024.10577779","title":"A Comparative Study of Text-to-Image Generative Models","year":2024,"lang":"en","type":"article","venue":"","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Generative grammar; Natural language processing; Image (mathematics); 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":[0.003117438,0.0007944752,0.0006900198,0.001041914,0.0003385546,0.001345562,0.001420847,0.001378275,0.003104216],"category_scores_gemma":[0.01231353,0.0003732896,0.0009714859,0.0006047687,0.000933944,0.002319516,0.0008381862,0.001273289,0.0006123871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001853966,"about_ca_system_score_gemma":0.0006936782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00464608,"about_ca_topic_score_gemma":0.004134174,"domain_scores_codex":[0.9990155,0.0004128359,0.00004265453,0.000174274,0.0002720052,0.00008283336],"domain_scores_gemma":[0.9899776,0.008087743,0.0003796527,0.0006455556,0.0006862133,0.0002232204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002015691,0.0001223978,0.002088271,0.0002302437,0.0000858526,0.000142188,0.0001770911,0.9190513,0.001936782,0.02848791,0.002385181,0.04509124],"study_design_scores_gemma":[0.000007734747,0.00005768242,0.0003924006,0.00001756787,0.00001055538,0.0000520921,0.00002137568,0.9921301,0.0008791863,0.005564392,0.000857248,0.00000962794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3875676,0.00883407,0.5504035,0.004616841,0.0004210199,0.0003771249,0.001118955,0.002473445,0.04418744],"genre_scores_gemma":[0.950066,0.00205017,0.04031051,0.0003163976,0.0000996888,0.0001268301,0.0009252633,0.0002763034,0.005828885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00464608,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04162286459076366,"score_gpt":0.2971235440903709,"score_spread":0.2555006794996073,"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."}}