{"id":"W3163187961","doi":"10.1088/1742-6596/1903/1/012041","title":"Map style transfer using pixel-to-pixel model","year":2021,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Discriminator; Computer science; Artificial intelligence; Focus (optics); Pixel; Image (mathematics); Field (mathematics); Process (computing); Task (project management); Generator (circuit theory); Computer vision; Transfer (computing); Transfer of learning; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001271157,0.0001485146,0.0002827248,0.00006080618,0.0001227338,0.0002821018,0.000523253,0.00002856034,0.00002267505],"category_scores_gemma":[0.00002437881,0.000134873,0.0001241396,0.0002555421,0.00004708289,0.002214372,0.0001431736,0.0002453623,0.00001334385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003645535,"about_ca_system_score_gemma":0.0005259002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.805085e-7,"about_ca_topic_score_gemma":0.000001589179,"domain_scores_codex":[0.9987995,0.00004457522,0.0003402938,0.0002001121,0.0003752595,0.0002402854],"domain_scores_gemma":[0.9986303,0.00002658494,0.0001069743,0.0002954729,0.0007792859,0.0001614112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002808667,0.0001166419,0.00002927197,0.00003056133,0.00003603752,0.00005334039,0.003803033,0.01595639,0.6003711,0.1814476,0.0001615676,0.1979663],"study_design_scores_gemma":[0.0005543686,0.0001611153,0.00005122229,0.0002526731,0.00002445785,0.0001898693,0.0008796427,0.4236502,0.468201,0.1008437,0.004784429,0.0004073875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01423715,0.00008173869,0.9832692,0.001652033,0.0003486885,0.00003572694,0.000002979395,0.00002053071,0.0003519458],"genre_scores_gemma":[0.6521075,0.00003782512,0.3468489,0.0005600269,0.0001254744,5.441403e-7,4.302698e-7,0.00001041031,0.000308952],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6378703,"threshold_uncertainty_score":0.549996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846154458194416,"score_gpt":0.2960156401303979,"score_spread":0.2475540955484538,"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."}}