{"id":"W2897191831","doi":"10.1109/wetice.2018.00035","title":"Investigating Plausible Reasoning Over Knowledge Graphs for Semantics-Based Health Data Analytics","year":2018,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Semantics (computer science); Correctness; Knowledge graph; Analytics; Model-based reasoning; Analytic reasoning; Reasoning system; Data science; Information retrieval; Artificial intelligence; Knowledge representation and reasoning; Programming language","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":[0.0009723245,0.0001588156,0.0002541759,0.0001448172,0.0003706976,0.0002251995,0.001636316,0.00006002475,0.00001244371],"category_scores_gemma":[0.0004151944,0.0001336501,0.00004957023,0.0005566865,0.0001554816,0.0004532298,0.0005890052,0.00008654239,0.00002268166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003343976,"about_ca_system_score_gemma":0.0005301482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002472511,"about_ca_topic_score_gemma":0.001464706,"domain_scores_codex":[0.9983678,0.00005414983,0.000321697,0.0005925688,0.0001853751,0.0004784304],"domain_scores_gemma":[0.9979552,0.0003661249,0.0001610441,0.001219733,0.0001487275,0.0001491809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006023395,0.0001242415,0.03582583,0.0002519326,0.00005888002,0.000001792177,0.0009455533,0.00006390024,0.0002076576,0.8644378,0.08404677,0.01402962],"study_design_scores_gemma":[0.0004261321,0.0001968798,0.003772537,0.0001227827,0.000009929793,0.000002977491,0.00006690446,0.9791553,0.001214766,0.008661176,0.006173373,0.0001972293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01264649,0.0002796401,0.9817464,0.002361939,0.0004786924,0.000261715,0.0000121763,0.0003960189,0.001816881],"genre_scores_gemma":[0.3428977,0.000007055994,0.6544774,0.002201088,0.0001473603,0.000005716301,0.00002639155,0.00001209125,0.0002251758],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9790914,"threshold_uncertainty_score":0.5450094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1401794276338126,"score_gpt":0.3709340636642858,"score_spread":0.2307546360304731,"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."}}