{"id":"W3200914972","doi":"10.5539/ells.v11n4p1","title":"The Spatial Cognitive Meaning of Across","year":2021,"lang":"en","type":"article","venue":"English Language and Literature Studies","topic":"Categorization, perception, and language","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cognitive grammar; Covert; Spatial relation; Schema (genetic algorithms); Relation (database); Landmark; Image schema; Spatial analysis; Cognition; Meaning (existential); Grammar; Cognitive linguistics; Computer science; Linguistics; Cognitive map; Artificial intelligence; Psychology; Mathematics; Information retrieval; Philosophy; Statistics; Data mining","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":[0.0002004598,0.0001185614,0.0001820446,0.00001960611,0.0002973897,0.00008406492,0.00005447629,0.00007135827,0.0001406564],"category_scores_gemma":[0.0006058901,0.00007912487,0.00005500295,0.0002034593,0.0001594155,0.00006921071,0.00006425352,0.0001570093,0.000003201481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006509143,"about_ca_system_score_gemma":0.00001043655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005500888,"about_ca_topic_score_gemma":0.0007191977,"domain_scores_codex":[0.9991888,0.0001266868,0.0001739989,0.0002151279,0.0001048951,0.000190426],"domain_scores_gemma":[0.9989569,0.0003066706,0.00006505767,0.0001607327,0.0004825502,0.00002810128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004066083,0.00002743723,0.001642536,0.00002977645,0.0002209135,0.000116762,0.9775147,1.128931e-7,0.0002252182,0.004126171,0.001009415,0.01504629],"study_design_scores_gemma":[0.0006111812,0.0000432061,0.009752447,0.0001076283,0.00004783531,0.00002514013,0.9810599,7.740815e-7,0.0005750185,0.0001283651,0.007525899,0.0001225906],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8855862,0.1011957,0.00004712464,0.00006302651,0.001041216,0.00008678667,0.00011322,0.00004047227,0.01182624],"genre_scores_gemma":[0.99202,0.0009244686,0.0000174178,0.0000970995,0.0009622764,0.00001637301,0.0001081499,0.0000116341,0.005842597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1064338,"threshold_uncertainty_score":0.3226619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129859454531258,"score_gpt":0.3319506065845235,"score_spread":0.320652012039211,"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."}}