{"id":"W2092324613","doi":"10.1007/s007780200062","title":"Query processing techniques for arrays","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Variety (cybernetics); Class (philosophy); Rewriting; Query plan; Function (biology); Query optimization; Data structure; Space (punctuation); Theoretical computer science; Programming language; Database; Information retrieval; Sargable; Artificial intelligence; Search engine; Web search query","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":[0.0004390531,0.00007879466,0.0000955267,0.00004428423,0.0005078322,0.0001469659,0.0004237339,0.0000215229,0.00001297566],"category_scores_gemma":[0.00004051473,0.00004524009,0.00005364082,0.000124799,0.00004106115,0.0007673635,0.00006419055,0.0001526607,0.000009507266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000212751,"about_ca_system_score_gemma":0.00002195632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001830717,"about_ca_topic_score_gemma":0.000001352278,"domain_scores_codex":[0.9993262,0.00003417115,0.0001811028,0.0001088857,0.0001475622,0.0002020408],"domain_scores_gemma":[0.9994278,0.00004797008,0.0001410674,0.000245988,0.00008670949,0.0000504558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007593922,0.00004226156,0.00003434497,0.00003897996,0.00001533403,0.00001897259,0.002007434,0.00004591509,0.004299584,0.07602889,0.0239795,0.8934812],"study_design_scores_gemma":[0.0002468844,0.0001345866,0.00003339293,0.000193431,0.000008236284,0.001590154,0.0002064171,0.02863702,0.01272949,0.01513624,0.940834,0.0002501458],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003111582,0.000998411,0.9949465,0.002150928,0.0001984246,0.0001119312,0.000002454474,0.00009940589,0.001180779],"genre_scores_gemma":[0.107095,0.0002221051,0.8891156,0.0008504358,0.001275421,0.00004421285,6.659638e-7,0.00001975742,0.001376837],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9168545,"threshold_uncertainty_score":0.3905886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430227086175861,"score_gpt":0.2687840089182429,"score_spread":0.2344817380564843,"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."}}