{"id":"W2687745869","doi":"10.1109/ccece.2017.7946720","title":"AEIPA: Docker-based system for Automated Evaluation of Image Processing Algorithms","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Benchmark (surveying); Plug-in; Task (project management); Overhead (engineering); Image processing; Principal (computer security); Scratch; Image (mathematics); Embedded system; Artificial intelligence; Data mining; Algorithm; Operating system; Engineering","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":[0.001138345,0.0001095908,0.0001794129,0.00007547373,0.0003146522,0.0002752292,0.00080455,0.00005114036,0.000002664582],"category_scores_gemma":[0.0003026526,0.00008986801,0.00006391247,0.0001036404,0.00006133624,0.001305794,0.0001033358,0.00004053176,0.000003296297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007975789,"about_ca_system_score_gemma":0.0001995643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001763263,"about_ca_topic_score_gemma":0.000001128115,"domain_scores_codex":[0.9988136,0.00004090943,0.0002560955,0.0002853538,0.0004227939,0.000181205],"domain_scores_gemma":[0.9977453,0.00004670318,0.0003610108,0.0007336701,0.001072226,0.00004107602],"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":[0.00001875944,0.00007976311,0.00007442178,0.0004455328,0.00001350815,0.000003206977,0.00008683294,0.0001063558,0.02657162,0.003137815,0.0007724379,0.9686897],"study_design_scores_gemma":[0.0004122225,0.00005575887,0.0002382345,0.00008735703,0.00001307149,0.000001671002,0.00001083928,0.6331773,0.3651324,0.0007004591,0.00009361159,0.00007715069],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008830458,0.00007323155,0.9946579,0.0001633197,0.0001000329,0.0006276554,0.00000401548,0.001178359,0.002312495],"genre_scores_gemma":[0.5161372,6.769354e-7,0.4837277,0.00001603067,0.00001978667,0.0000576421,0.000002102708,0.000006289032,0.00003255364],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9686126,"threshold_uncertainty_score":0.3664711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06193896251141947,"score_gpt":0.3958497127733764,"score_spread":0.333910750261957,"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."}}