{"id":"W3094746467","doi":"10.1075/ml.00012.tar","title":"On <i>twittizens</i> and <i>city residents</i>","year":2020,"lang":"en","type":"article","venue":"The Mental Lexicon","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Access Alliance Multicultural Health and Community Services","funders":"","keywords":"Semantic property; Natural language processing; Compounding; Semantic interpretation; Computer science; Perception; Interpretation (philosophy); Viewpoints; Transparency (behavior); Linguistics; Artificial intelligence; Information retrieval; Psychology; Materials science; 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":[0.0003981383,0.0002384264,0.0002485185,0.0005301655,0.001446543,0.00123336,0.0002603547,0.0002945025,0.00721563],"category_scores_gemma":[0.001311909,0.0000996515,0.0001391708,0.0007518812,0.0009729498,0.0007532861,0.0009561513,0.0004675758,0.0006970772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137154,"about_ca_system_score_gemma":0.0003552271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05582868,"about_ca_topic_score_gemma":0.1043272,"domain_scores_codex":[0.9997436,0.00009278896,0.00001062894,0.00005007255,0.00005986936,0.00004305112],"domain_scores_gemma":[0.9994623,0.0002061029,0.0001233869,0.00003423549,0.0001178138,0.00005604314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0009871217,0.0003818519,0.2267892,0.0003290617,0.00007363867,0.002887586,0.6611066,0.0002989491,0.03771874,0.003100622,0.003935415,0.06239123],"study_design_scores_gemma":[0.0000122725,0.0002240469,0.439074,0.000115796,0.00004254119,0.0003117712,0.5354483,0.0004218657,0.006021638,0.0008224656,0.01744994,0.00005550496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937603,0.00003412446,0.00009419945,0.00004769241,0.00000638633,0.000006896338,0.00007876696,0.000003081061,0.00596856],"genre_scores_gemma":[0.9971159,0.0000636156,0.0001529256,0.00003823733,0.000003510627,0.00001161332,0.0001219093,0.000007480243,0.002484789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05582868,"threshold_uncertainty_score":0.1110075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947997256696449,"score_gpt":0.3094050375363376,"score_spread":0.2699250649693731,"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."}}