{"id":"W2543432111","doi":"10.1109/wifs.2009.5386469","title":"Towards automated image hashing based on the Fast Johnson-Lindenstrauss Transform (FJLT)","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Hash function; Benchmark (surveying); Image (mathematics); Artificial intelligence; Search engine indexing; Set (abstract data type); Locality-sensitive hashing; Digital image; Algorithm; Image processing; Hash table; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001382563,0.0005306135,0.0006288544,0.001329038,0.0004319824,0.001018287,0.001111931,0.0008030712,0.001301976],"category_scores_gemma":[0.005732801,0.0004037986,0.0003948663,0.001241221,0.00108517,0.002356301,0.001304828,0.001065327,0.001080896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004971526,"about_ca_system_score_gemma":0.001015963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001270876,"about_ca_topic_score_gemma":0.001305048,"domain_scores_codex":[0.9990211,0.000246953,0.000053287,0.0001141155,0.000512331,0.00005232825],"domain_scores_gemma":[0.9976102,0.0008065189,0.0003331703,0.0005474016,0.0006257371,0.00007680761],"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":[0.0003496314,0.0001963995,0.001842524,0.0002607094,0.00005883186,0.0001399232,0.0002926634,0.08303806,0.1100043,0.04527525,0.005504245,0.7530375],"study_design_scores_gemma":[0.00007026001,0.0003871832,0.001006326,0.00002406745,0.00002426468,0.0006759182,0.00008267071,0.9105426,0.06077253,0.01765378,0.008685979,0.00007435615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01373009,0.0003392579,0.9843336,0.00010662,0.00004073982,0.00005861389,0.00001825316,0.0006702355,0.0007025565],"genre_scores_gemma":[0.1397225,0.0003596781,0.8581607,0.000101893,0.0000903644,0.00007465119,0.0001387364,0.00005905756,0.001292519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001382563,"threshold_uncertainty_score":0.007311761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01840280522154131,"score_gpt":0.2925554824353324,"score_spread":0.2741526772137911,"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."}}