{"id":"W2585282790","doi":"","title":"Extracting Conceptual Relationships from Specialized Documents","year":2008,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Conceptual model; Representation (politics); Data science; Simple (philosophy); Information extraction; Management science; Information retrieval; Knowledge management; Database","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":[0.0008368161,0.0009334774,0.0008119948,0.009958575,0.001470371,0.003967726,0.001473333,0.001443478,0.00852126],"category_scores_gemma":[0.008481425,0.0006631432,0.001370438,0.009224013,0.0007280706,0.006427228,0.002091012,0.001679038,0.004864676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243372,"about_ca_system_score_gemma":0.00263382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005661615,"about_ca_topic_score_gemma":0.007211034,"domain_scores_codex":[0.9987142,0.0001837722,0.0001930061,0.0003777993,0.000412204,0.0001190378],"domain_scores_gemma":[0.9962928,0.001740044,0.0004085159,0.0006560564,0.0007358139,0.0001667895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004243947,0.0004471653,0.01413299,0.002169129,0.0001552998,0.002995518,0.00461647,0.003654585,0.03655405,0.05709529,0.03641059,0.8413445],"study_design_scores_gemma":[0.0002272614,0.0004354998,0.03495402,0.001902369,0.00132713,0.007198718,0.0220168,0.1663939,0.09811591,0.1302535,0.5369471,0.0002278603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3083534,0.006707642,0.6015921,0.001990094,0.0004145432,0.001237405,0.03597524,0.01035951,0.03337006],"genre_scores_gemma":[0.5033018,0.003317027,0.4193595,0.0001904893,0.0001912638,0.0003884984,0.06376109,0.0008999532,0.008590296],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009958575,"threshold_uncertainty_score":0.02850646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1476415459603331,"score_gpt":0.2732777941133869,"score_spread":0.1256362481530538,"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."}}