{"id":"W1559127666","doi":"","title":"Sticking one’s nose in the data : Evaluation in phraseological sequences with nose","year":2007,"lang":"en","type":"article","venue":"Malmö University Publications (Malmö University)","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nose; Linguistics; Germanic languages; Computer science; Natural language processing; Artificial intelligence; Geology; Philosophy; Paleontology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002060576,0.0001807583,0.000193017,0.001380034,0.0003250157,0.00005982873,0.001531237,0.0001907677,0.0009253211],"category_scores_gemma":[0.0001683676,0.0001692696,0.00004619556,0.003457774,0.000291879,0.001038702,0.000251322,0.0004308931,0.00009169328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004011335,"about_ca_system_score_gemma":0.0002251436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001491092,"about_ca_topic_score_gemma":0.01110843,"domain_scores_codex":[0.9975092,0.0007148212,0.0001928837,0.0006762576,0.0004491393,0.0004577061],"domain_scores_gemma":[0.998,0.0004431488,0.0001655309,0.001007715,0.0002805477,0.0001030846],"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":[0.001239729,0.003383771,0.2677297,0.00003120942,0.0002605877,0.001477825,0.01568381,0.0001832127,0.0002868055,0.6823514,0.001908897,0.02546311],"study_design_scores_gemma":[0.004122021,0.0002113188,0.8028993,0.00005319346,0.0003751893,0.00006309261,0.1100805,0.0007358688,0.00002404977,0.0006096257,0.08028793,0.0005378603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7806274,0.00004411429,0.007554626,0.002050693,0.00008651627,0.0007469284,0.00009472518,0.0001004089,0.2086946],"genre_scores_gemma":[0.9947337,0.00002071791,0.000743609,0.0001836488,0.000047072,0.000001197557,0.0006152862,0.000008668353,0.003646128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6817417,"threshold_uncertainty_score":0.999988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1049030719983054,"score_gpt":0.3102794422677561,"score_spread":0.2053763702694507,"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."}}