{"id":"W2905213535","doi":"10.5430/air.v7n2p55","title":"Knowledge representation with T","year":2018,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Linguistic Studies and Language Acquisition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Vocabulary; Representation (politics); Human language; Set (abstract data type); Semantics (computer science); Knowledge representation and reasoning; Linguistics; Natural language processing; Tacit knowledge; Natural language; Artificial intelligence; Programming language; Knowledge management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002636844,0.0007407633,0.0007828238,0.002052016,0.00124455,0.008683859,0.002360416,0.00176942,0.01631357],"category_scores_gemma":[0.01223379,0.0005178479,0.002411243,0.003576132,0.003402672,0.01169126,0.006307944,0.002849786,0.006636805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328792,"about_ca_system_score_gemma":0.002365566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003011934,"about_ca_topic_score_gemma":0.001758641,"domain_scores_codex":[0.9962454,0.001430174,0.0004767226,0.0009289994,0.000673259,0.0002454408],"domain_scores_gemma":[0.9942172,0.001993762,0.0003721183,0.00256549,0.0006213619,0.0002299877],"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":[0.0001102511,0.00005409829,0.000306615,0.0004064546,0.00007534535,0.0003552916,0.001064022,0.00581154,0.001481151,0.7809197,0.01888674,0.1905288],"study_design_scores_gemma":[0.00003847459,0.00005276451,0.0001098209,0.0001645718,0.00006345051,0.0004772901,0.0003349389,0.02877677,0.002662133,0.788422,0.1788579,0.00003994865],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002919091,0.0007429284,0.9505187,0.00263631,0.0003422384,0.0002173653,0.0007039462,0.002855642,0.03906368],"genre_scores_gemma":[0.1618661,0.001832092,0.8019922,0.001915652,0.0005164478,0.000622471,0.003212221,0.0005897409,0.02745303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01631357,"threshold_uncertainty_score":0.05457437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2481272748575234,"score_gpt":0.4754100029862705,"score_spread":0.227282728128747,"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."}}