{"id":"W4281397844","doi":"10.1145/3530800.3534531","title":"Universal provenance for regular path queries","year":2022,"lang":"en","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Provenance; Computer science; Tuple; SPARQL; Path (computing); Path expression; Relational algebra; Homomorphic encryption; Theoretical computer science; Relational database; Information retrieval; Mathematics; Query language; RDF; Discrete mathematics; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01019403,0.0005474294,0.001190122,0.001670303,0.002083655,0.00438133,0.001882897,0.001590427,0.002173454],"category_scores_gemma":[0.05179495,0.0006113995,0.001807545,0.002668407,0.006044,0.01527944,0.004570403,0.003027462,0.0003660116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002559614,"about_ca_system_score_gemma":0.002496817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004255242,"about_ca_topic_score_gemma":0.002070111,"domain_scores_codex":[0.988234,0.003552899,0.000914979,0.002366441,0.003828798,0.00110273],"domain_scores_gemma":[0.9560519,0.02707277,0.00303036,0.008082126,0.005035885,0.0007269413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001472831,0.00005576524,0.001842242,0.0002312668,0.0000419451,0.0004550838,0.001340531,0.0231271,0.002701224,0.9483619,0.001006364,0.02068935],"study_design_scores_gemma":[0.00002168745,0.00004401119,0.00023347,0.00004199621,0.00003743644,0.0003122812,0.000277372,0.08309601,0.004131875,0.9064474,0.00532885,0.00002764465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06439016,0.0005205664,0.9278229,0.001283333,0.0001027716,0.0001362894,0.0002890536,0.0005539556,0.004900981],"genre_scores_gemma":[0.796677,0.0008046036,0.19796,0.0004220538,0.0002817666,0.0001597808,0.0006544563,0.0002917012,0.00274854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01019403,"threshold_uncertainty_score":0.05391186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1169502304382312,"score_gpt":0.3604582865032122,"score_spread":0.243508056064981,"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."}}