{"id":"W4380481974","doi":"10.6000/1929-4409.2020.09.290","title":"Dictionary of Abstract the Words of the Russian Language: Nouns with High Numerical Measure of Abstractness","year":2022,"lang":"en","type":"article","venue":"International Journal of Criminology and Sociology","topic":"Discourse Analysis and Cultural Communication","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kazan Federal University","keywords":"Polysemy; Computer science; Vocabulary; Noun; Natural language processing; Context (archaeology); Point (geometry); Linguistics; Abstraction; Task (project management); Proper noun; Artificial intelligence; Word (group theory); Measure (data warehouse); Mathematics; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006435106,0.0000436569,0.0001693491,0.00004428836,0.0001989031,0.000003615855,0.0005891894,0.00005442156,0.0002816211],"category_scores_gemma":[0.00007797625,0.00002316934,0.0000989665,0.00002996245,0.001038112,0.00006670378,0.00007029933,0.0003040731,1.544934e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000282736,"about_ca_system_score_gemma":0.000158056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005382446,"about_ca_topic_score_gemma":0.00006344158,"domain_scores_codex":[0.9988764,0.0003786813,0.0003008453,0.00004867166,0.00032961,0.00006582626],"domain_scores_gemma":[0.9987351,0.0002468591,0.0007037139,0.00009053062,0.0002088796,0.00001487897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005438305,0.0004498725,0.02333475,0.00000880741,0.001306154,0.00001350883,0.09844372,0.0008756083,0.003490395,0.8609959,0.0002786304,0.01025885],"study_design_scores_gemma":[0.0006004112,0.0003066518,0.8835721,0.00002972665,0.0002575512,0.00009757546,0.07080917,0.000009925771,0.0005207841,0.04167847,0.002038874,0.00007874866],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799531,0.0006399325,0.00002099271,0.01733678,0.0002294747,0.00003287022,0.00001241068,0.000001294924,0.00177313],"genre_scores_gemma":[0.9995508,0.0001382922,0.00003548004,0.0001140381,0.00007278314,0.0000020092,0.00000280388,0.000001962381,0.00008190034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8602374,"threshold_uncertainty_score":0.3824965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03555547684059428,"score_gpt":0.3342556257088874,"score_spread":0.2987001488682931,"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."}}