{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00121591,0.0003730258,0.0002153464,0.001438915,0.001304355,0.00361162,0.000577568,0.000585546,0.004809066],"category_scores_gemma":[0.003137167,0.0002566969,0.000504224,0.0009701244,0.00718451,0.007981687,0.001700576,0.001121621,0.0005246869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00125341,"about_ca_system_score_gemma":0.0007530528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003188444,"about_ca_topic_score_gemma":0.002549897,"domain_scores_codex":[0.9988223,0.0003968959,0.000107711,0.000337224,0.0002578302,0.00007802103],"domain_scores_gemma":[0.998422,0.0005700031,0.0002334998,0.0003286299,0.000384707,0.00006112194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005525281,0.00001955518,0.003752988,0.0002379842,0.00001923521,0.0003977364,0.03816462,0.000202472,0.007421863,0.9017234,0.001787214,0.04621777],"study_design_scores_gemma":[0.00002700394,0.0001977248,0.026774,0.0004765502,0.000131973,0.002649602,0.09535696,0.003090543,0.01117946,0.5292635,0.3307356,0.0001171152],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3528589,0.002113291,0.1575418,0.004040063,0.0003846148,0.00008836831,0.000490404,0.0003218805,0.4821605],"genre_scores_gemma":[0.9751028,0.0005835058,0.01538613,0.000282133,0.00004505878,0.00002271556,0.0002468336,0.00009783049,0.008232943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004809066,"threshold_uncertainty_score":0.01608789,"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."}}