{"id":"W3186910762","doi":"10.1109/tip.2022.3160602","title":"Scalable Image Coding for Humans and Machines","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Codec; Scalability; Artificial intelligence; Coding (social sciences); Computer vision; Machine vision; Machine learning; Task (project management); Computer hardware; Database; 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002750657,0.0001647802,0.0001661921,0.0001923309,0.00157499,0.0003569352,0.0003798566,0.00002588149,0.00002955232],"category_scores_gemma":[0.00001081089,0.0001701839,0.00006997752,0.0004278802,0.00008125203,0.001553026,0.00001309622,0.0002773582,0.000002396094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000685732,"about_ca_system_score_gemma":0.00006184261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007420593,"about_ca_topic_score_gemma":0.000001687023,"domain_scores_codex":[0.9988074,0.00003811042,0.0002084656,0.0004430321,0.0002142422,0.0002887843],"domain_scores_gemma":[0.9994105,0.00009246545,0.0000857241,0.0002437574,0.0001027391,0.00006488057],"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":[0.00005443331,0.0001805498,0.000006110153,0.0001908588,0.00001305815,0.0000147058,0.0007625477,0.0002058085,0.1374791,0.0003532064,0.0003566754,0.860383],"study_design_scores_gemma":[0.001088189,0.0005420066,0.0000322362,0.00009466768,0.0000443454,0.000117572,0.000244026,0.2165877,0.7618147,0.01325014,0.005503143,0.0006812985],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006578437,0.0002348789,0.9972026,0.0005200668,0.0001427151,0.0003027382,0.00002440843,0.0004919647,0.0004227607],"genre_scores_gemma":[0.5093091,0.00004511134,0.4892448,0.0003908453,0.0000294392,0.0002631751,0.000001611139,0.00002950219,0.0006864642],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8597016,"threshold_uncertainty_score":0.9997248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02030060063684558,"score_gpt":0.3022955667161125,"score_spread":0.2819949660792669,"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."}}