{"id":"W2573487579","doi":"","title":"Text Processing Chains: Getting Help from Typed Applicative Systems.","year":2016,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Programming language; Natural language processing","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":[0.007065033,0.00140479,0.001064995,0.003024579,0.001871431,0.006130173,0.002729615,0.002976592,0.03127967],"category_scores_gemma":[0.05132727,0.001246285,0.001175561,0.003576282,0.001805795,0.02024753,0.005732217,0.003012263,0.02173796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007923609,"about_ca_system_score_gemma":0.002163143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002566243,"about_ca_topic_score_gemma":0.004162471,"domain_scores_codex":[0.9961782,0.001605458,0.0003810813,0.000646215,0.0009737806,0.0002153662],"domain_scores_gemma":[0.9626503,0.02451583,0.0008457691,0.00648414,0.004580363,0.0009234961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007196328,0.0002667389,0.002192801,0.0009432441,0.0001008619,0.0006562744,0.003522541,0.005654321,0.007379441,0.09752151,0.09084605,0.7901967],"study_design_scores_gemma":[0.0001203121,0.000107716,0.000524617,0.0005572663,0.0001936402,0.0005659699,0.002231913,0.09055719,0.02740054,0.5776407,0.2999892,0.0001108894],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01070354,0.002262835,0.9313922,0.003720919,0.0006543843,0.0001841334,0.001732472,0.02564187,0.0237077],"genre_scores_gemma":[0.1056023,0.002577794,0.8510818,0.0008878207,0.0004920546,0.0002139762,0.004775784,0.006823289,0.02754509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03127967,"threshold_uncertainty_score":0.1046408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07319901152962512,"score_gpt":0.3556524837275419,"score_spread":0.2824534721979168,"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."}}