{"id":"W2604217576","doi":"","title":"Word embeddings and Global Preference for Contextual Suggestion.","year":2016,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University; Université Laval","funders":"","keywords":"Preference; Computer science; Word (group theory); Natural language processing; Artificial intelligence; Speech recognition; Linguistics; Mathematics; Statistics; Philosophy","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":[0.001724369,0.0003452922,0.0002971024,0.0009123207,0.0003888021,0.002382191,0.0004426503,0.0008560479,0.008598678],"category_scores_gemma":[0.03225145,0.0002436102,0.0002656697,0.000903325,0.0006479841,0.004293395,0.001065464,0.001203605,0.0009996092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004091698,"about_ca_system_score_gemma":0.0003564442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007498011,"about_ca_topic_score_gemma":0.001011368,"domain_scores_codex":[0.9987527,0.0005923565,0.00009228885,0.0002463471,0.0002091145,0.0001072775],"domain_scores_gemma":[0.9878649,0.007458156,0.001528482,0.001092431,0.001385537,0.0006705104],"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":[0.007291966,0.001182257,0.136025,0.002196233,0.0007117398,0.0008367235,0.00732712,0.008990762,0.1642216,0.08844464,0.01804306,0.564729],"study_design_scores_gemma":[0.0009900099,0.003413072,0.4308605,0.0006498081,0.001496157,0.003548996,0.01016797,0.1776686,0.04474949,0.2978743,0.02795039,0.0006307028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9280536,0.002311602,0.03885195,0.001068119,0.0002483979,0.0001136044,0.0005296944,0.0004464721,0.02837654],"genre_scores_gemma":[0.9925956,0.0002314254,0.005284213,0.00008453761,0.00004792555,0.00002400418,0.0003615155,0.00008828781,0.00128253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008598678,"threshold_uncertainty_score":0.02876544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05459598172282607,"score_gpt":0.3217472922575974,"score_spread":0.2671513105347713,"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."}}