{"id":"W4403499910","doi":"10.1007/978-3-031-72845-7","title":"Computational Color Imaging","year":2024,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Universität Greifswald; Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; Universidade do Minho; National Taiwan University of Science and Technology; National Taiwan University; Chiba University; Chulalongkorn University; Universidad de Granada; Università degli Studi di Pavia; York University; Université de Bourgogne; Ministerio de Ciencia e Innovación; Università degli Studi di Milano; Conselleria d'Educació, Investigació, Cultura i Esport; University of East Anglia; University of Dayton","keywords":"Computer science; Artificial intelligence; Computer vision; Computer graphics (images)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008706062,0.0004186954,0.0003770562,0.0009940126,0.000211509,0.001289837,0.003250267,0.0001811157,0.0000154655],"category_scores_gemma":[0.00007717329,0.0003749477,0.000138686,0.00170121,0.0006903561,0.0006988037,0.001335806,0.0008249175,0.0002355267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007182721,"about_ca_system_score_gemma":0.002103593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005948409,"about_ca_topic_score_gemma":0.000003231007,"domain_scores_codex":[0.9963055,0.0000449736,0.0004932502,0.00149167,0.001103692,0.0005609551],"domain_scores_gemma":[0.9980151,0.0004270925,0.0001802272,0.0009037968,0.0003365751,0.000137225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002694364,0.00004302064,0.00002093724,0.0001156463,0.00001066885,0.0001887537,0.0005140079,0.00502536,0.0001999587,0.04402753,0.001645522,0.9482059],"study_design_scores_gemma":[0.00006541802,0.00003462451,0.00003443059,0.0002324668,0.000004457144,0.00007837293,6.428497e-8,0.6522538,0.001740077,0.338402,0.006802865,0.0003513892],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00000324361,0.0009840444,0.9896956,0.002711015,0.001658401,0.0003276597,0.000007341684,0.0007165688,0.003896126],"genre_scores_gemma":[0.01834827,0.00003448128,0.9736752,0.003245729,0.0006923128,0.00003469977,0.0000249941,0.00005170002,0.003892631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9478545,"threshold_uncertainty_score":0.9998702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122217790472537,"score_gpt":0.2666234937261848,"score_spread":0.2544017146789311,"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."}}