{"id":"W4392194277","doi":"10.52058/2695-1592-2024-2(33)-449-459","title":"TENDENCIES IN THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE PROCESSING OF PHOTO MATERIALS","year":2024,"lang":"en","type":"article","venue":"Věda a perspektivy","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centennial College","funders":"","keywords":"Computer science; Artificial intelligence; Image processing; Process (computing); Machine learning; Artificial neural network; Retraining; Adaptation (eye); Deep learning; Data processing; Image (mathematics); Database","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":[0.0004360517,0.00007537648,0.000108994,0.0001245025,0.00001249635,0.00002756487,0.0002422751,0.00003433666,0.00002286329],"category_scores_gemma":[0.00004361718,0.00004686768,0.00002089824,0.0005353906,0.0000682422,0.0001100871,0.00001761938,0.0001061486,0.000003923479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002959585,"about_ca_system_score_gemma":0.00001533608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007783771,"about_ca_topic_score_gemma":0.00004143463,"domain_scores_codex":[0.9993532,0.00003391311,0.0002670296,0.0001023946,0.000145773,0.00009767866],"domain_scores_gemma":[0.9996915,0.00008058773,0.00002825486,0.000169759,0.00002519926,0.000004704734],"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":[0.000007721475,0.00003464808,0.00002001651,0.0003153831,0.000002758925,0.000004298,0.01684988,0.0005052017,0.8756196,0.005652972,0.00005226388,0.1009352],"study_design_scores_gemma":[0.0000161103,0.00002608247,0.0003438433,0.000221035,0.000006780911,0.000007773273,0.01324497,0.02399068,0.9495903,0.01189544,0.0005584704,0.00009850505],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6341282,0.003176768,0.3582022,0.0004367543,0.0001183162,0.001133501,0.00003006031,0.0002729092,0.002501305],"genre_scores_gemma":[0.9964737,0.00007494655,0.003281006,0.00001597062,0.00002647368,0.0001113641,0.000001973646,0.00001097876,0.000003582174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3623455,"threshold_uncertainty_score":0.1911209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847488742108956,"score_gpt":0.2968575091534411,"score_spread":0.2783826217323515,"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."}}