{"id":"W2946207881","doi":"10.1007/978-3-030-18305-9_52","title":"Name2Vec: Personal Names Embeddings","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Task (project management); Word (group theory); Information retrieval; Proper noun; Linkage (software); Natural language processing; Embedding; Artificial intelligence; Linguistics","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":[0.0006479927,0.002061772,0.0006765675,0.001436378,0.0005436124,0.001679757,0.001079853,0.001075832,0.0367817],"category_scores_gemma":[0.003018401,0.0007845508,0.001242428,0.001800609,0.000383633,0.004105254,0.002356645,0.001797635,0.04090646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000440344,"about_ca_system_score_gemma":0.0007530101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002281088,"about_ca_topic_score_gemma":0.005778367,"domain_scores_codex":[0.9991266,0.0001706666,0.00006236985,0.0002759497,0.0002741192,0.00009029231],"domain_scores_gemma":[0.999229,0.0001652231,0.00004061269,0.000338375,0.0001812122,0.00004570128],"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":[0.0001279405,0.000091938,0.0007453582,0.0002892606,0.00006721231,0.00009303211,0.0000945013,0.006592368,0.00331089,0.0138833,0.4787939,0.4959102],"study_design_scores_gemma":[0.00005398942,0.0001524644,0.001984949,0.000251713,0.0000932472,0.0007939978,0.0002320333,0.2891024,0.02956044,0.09826658,0.5793713,0.0001368275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009317662,0.002040551,0.7672107,0.001481985,0.002921987,0.0002235542,0.06761595,0.1176644,0.03152321],"genre_scores_gemma":[0.08172312,0.002567268,0.6007953,0.001097525,0.0007277561,0.0005882363,0.2088678,0.01202916,0.09160391],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0367817,"threshold_uncertainty_score":0.1230471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07252391469650568,"score_gpt":0.3510771114085041,"score_spread":0.2785531967119984,"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."}}