{"id":"W2155632927","doi":"10.1109/13.883358","title":"A software system for laboratory experiments in image processing","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Education","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Software; Implementation; Image processing; Software engineering; Processing; Class (philosophy); Software framework; Overhead (engineering); Software system; Multimedia; Software development; Artificial intelligence; Programming language; Image (mathematics); Software construction","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":[0.00005316535,0.0001011552,0.00008089187,0.0001114379,0.0001121452,0.00004898278,0.00007760289,0.00005685064,0.00005314355],"category_scores_gemma":[0.00000128105,0.0001159369,0.00002731766,0.000263077,0.00001503797,0.0002284819,1.073078e-7,0.0000924084,0.00002663802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001960768,"about_ca_system_score_gemma":0.0001160229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009477225,"about_ca_topic_score_gemma":0.000003293705,"domain_scores_codex":[0.9994899,0.000007303184,0.0001624919,0.0001443255,0.00006038828,0.0001356148],"domain_scores_gemma":[0.9997308,0.00001207834,0.0000164232,0.0001405949,0.00005715389,0.00004291949],"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":[0.00002278763,0.000492295,0.000004240981,0.0006723795,0.000009075283,2.931992e-7,0.001167782,0.008535009,0.02978248,0.00002666014,0.001328924,0.957958],"study_design_scores_gemma":[0.0007212178,0.00006456832,0.0001058887,0.0008388719,0.00004670361,0.00001004207,0.001243249,0.06066335,0.9199972,0.0003004695,0.01535239,0.0006560235],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03321571,0.0001916381,0.9641397,0.00006039947,0.000206521,0.0004757977,0.00002959133,0.0008368718,0.0008437981],"genre_scores_gemma":[0.9415812,0.00001860092,0.05618289,0.00004452521,0.0000431917,0.001832347,0.000008117151,0.00003707465,0.0002520434],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.957302,"threshold_uncertainty_score":0.472777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00934709392471651,"score_gpt":0.2734917926580948,"score_spread":0.2641446987333783,"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."}}