{"id":"W2473285855","doi":"","title":"Medio adverbio, medio prefijo: la evolución de medio como modificador de verbos en español","year":2015,"lang":"es","type":"article","venue":"Boletín de la Real Academia Española/Boletín de la Real Academia Española","topic":"Spanish Linguistics and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Adverbial; Pronoun; Linguistics; Relation (database); Verb; History; Humanities; Mathematics; Philosophy; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.01486614,0.003252383,0.003744783,0.001070272,0.001789454,0.002088409,0.004673889,0.01417006,0.0007120225],"category_scores_gemma":[0.01097742,0.003152015,0.001353159,0.0007661978,0.004856165,0.0007894675,0.00218264,0.0223481,0.0004640988],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004427686,"about_ca_system_score_gemma":0.004318252,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01265387,"about_ca_topic_score_gemma":0.0007035452,"domain_scores_codex":[0.9770711,0.007231369,0.003390189,0.003048314,0.003576403,0.005682607],"domain_scores_gemma":[0.9816956,0.009374846,0.001925931,0.00185612,0.00101756,0.004129936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002940142,0.001481273,0.04472328,0.002182581,0.003234446,0.004521025,0.1739163,0.001012127,0.006035237,0.4515186,0.2982453,0.01018967],"study_design_scores_gemma":[0.007329891,0.0007137029,0.02523111,0.002257389,0.002533426,0.00101105,0.02058044,0.004662321,0.002058923,0.01011244,0.9196017,0.003907602],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5298622,0.0313333,0.0007083834,0.009967651,0.002226354,0.002761169,0.00209607,0.002313163,0.4187317],"genre_scores_gemma":[0.8990687,0.063275,0.002699456,0.004472873,0.01780432,0.0008081944,0.000304387,0.0009675234,0.0105996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6213564,"threshold_uncertainty_score":0.9995101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131805160788026,"score_gpt":0.3013021705057086,"score_spread":0.288121654426906,"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."}}