{"id":"W4323244241","doi":"10.5220/0011693800003393","title":"Automatically Generating Image Segmentation Datasets for Video Games","year":2023,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Image segmentation; Artificial intelligence; Computer vision; Segmentation; Image (mathematics); Scale-space segmentation; Computer graphics (images); Video game; Multimedia","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":[0.0003879444,0.002686296,0.001329426,0.006072746,0.0007928368,0.001436929,0.001957031,0.001914475,0.006146472],"category_scores_gemma":[0.001987333,0.001191981,0.001959812,0.002983351,0.0004541587,0.001060211,0.001370198,0.001551749,0.004578065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001321985,"about_ca_system_score_gemma":0.001535145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01845288,"about_ca_topic_score_gemma":0.04599595,"domain_scores_codex":[0.9994218,0.00005498866,0.00003304628,0.0002489,0.000140882,0.0001004474],"domain_scores_gemma":[0.9992199,0.000210653,0.00006752946,0.0001208047,0.0002939773,0.00008715806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001164778,0.001269796,0.007303247,0.001342626,0.0004653097,0.00113665,0.0003351407,0.0471887,0.09331807,0.005273094,0.1740905,0.6671121],"study_design_scores_gemma":[0.0001880905,0.0004232255,0.01778306,0.0002916742,0.0002036736,0.001004686,0.0006238455,0.8346731,0.08367433,0.01178296,0.04922745,0.0001238582],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2108823,0.002826486,0.5997685,0.0009000271,0.000890628,0.003133204,0.0888568,0.07263263,0.02010939],"genre_scores_gemma":[0.2349212,0.001111858,0.5637568,0.0003318182,0.0001218425,0.001132423,0.188622,0.002759492,0.007242559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01845288,"threshold_uncertainty_score":0.03669095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04500764184422271,"score_gpt":0.3471030050575727,"score_spread":0.30209536321335,"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."}}