{"id":"W2017988065","doi":"10.1145/1951365.1951374","title":"GPX-matcher","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; XML; Regular expression; Matching (statistics); Encoding (memory); Automaton; Path expression; XML database; Theoretical computer science; Information retrieval; Programming language; World Wide Web; Artificial intelligence","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":[0.0008312901,0.0009259669,0.00074211,0.001067546,0.0008033576,0.001800101,0.002473974,0.001669847,0.03533885],"category_scores_gemma":[0.003522787,0.000554654,0.0007043398,0.001565345,0.0005932847,0.003263673,0.002427739,0.001132922,0.01672531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008824781,"about_ca_system_score_gemma":0.001063521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001810973,"about_ca_topic_score_gemma":0.001367596,"domain_scores_codex":[0.9989367,0.0001510628,0.00008247222,0.0003763176,0.0003404123,0.0001129598],"domain_scores_gemma":[0.9990519,0.0002323742,0.00005298212,0.0004490524,0.0001776509,0.00003603717],"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":[0.001468226,0.0003559571,0.003333287,0.0007092428,0.0001452753,0.0006309866,0.0003553876,0.02179674,0.03135876,0.07974591,0.1549827,0.7051175],"study_design_scores_gemma":[0.0003481305,0.0005050973,0.002264133,0.0001209997,0.0001130389,0.00131501,0.0002732721,0.3723506,0.1215973,0.1330869,0.36791,0.0001154849],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.02006883,0.0005188228,0.8530591,0.0006129304,0.0004650449,0.0005454636,0.003271862,0.09954245,0.02191542],"genre_scores_gemma":[0.2172062,0.0005760276,0.6949042,0.001461577,0.0001753057,0.0007679006,0.01440549,0.007680371,0.06282298],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03533885,"threshold_uncertainty_score":0.1182202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0458915072464365,"score_gpt":0.2146078215773051,"score_spread":0.1687163143308686,"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."}}