{"id":"W1996845866","doi":"10.1142/s0218213006003089","title":"COORDINATION AND APPLICATIVE CATEGORIAL TYPE LOGIC","year":2006,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Categorial grammar; Combinatory categorial grammar; Conjunction (astronomy); Programming language; Type (biology); Process (computing); Artificial intelligence; Generative grammar; Theoretical computer science; Natural language processing; Link grammar; Mildly context-sensitive grammar formalism; Head-driven phrase structure grammar; Emergent grammar","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":[0.002412315,0.0004813046,0.0005824565,0.001907857,0.001582145,0.004197181,0.001058499,0.001323726,0.0045007],"category_scores_gemma":[0.002718453,0.0004074115,0.001228439,0.001795352,0.005731436,0.004644973,0.002222964,0.001550759,0.0007116355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003027759,"about_ca_system_score_gemma":0.001568651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005026704,"about_ca_topic_score_gemma":0.002376051,"domain_scores_codex":[0.9981179,0.0007124846,0.000134146,0.0003640376,0.0003909737,0.0002804755],"domain_scores_gemma":[0.9982161,0.0008988482,0.0002087717,0.0002942578,0.0002704859,0.0001115308],"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":[0.000006851054,0.000002643635,0.0001605547,0.00001638503,0.000004400538,0.00008246742,0.0001908249,0.0007392413,0.0002134054,0.9956412,0.0003857025,0.0025563],"study_design_scores_gemma":[0.00000873805,0.000007482809,0.0001749451,0.00001400003,0.000008963782,0.0001321932,0.00009711742,0.003458832,0.0002850343,0.986504,0.00929955,0.000009198502],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.121685,0.007292578,0.6597494,0.007278872,0.0008927489,0.0001142488,0.0004859623,0.00199052,0.2005107],"genre_scores_gemma":[0.9136348,0.001807234,0.0641093,0.0008076064,0.0004698467,0.00008427519,0.0002411578,0.0001931904,0.01865257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005026704,"threshold_uncertainty_score":0.02196801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04109751950976159,"score_gpt":0.3361296487219334,"score_spread":0.2950321292121718,"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."}}