{"id":"W4256561389","doi":"10.26686/wgtn.13670584.v1","title":"Lexical fixedness and compositionality in L1 speakers’ and L2 learners’ intuitions about word combinations: Evidence from Italian","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Victoria University; Faculty of Education, Victoria University of Wellington; Victoria University of Wellington","keywords":"Principle of compositionality; Verb; Linguistics; Noun; Sentence; Computer science; Psychology; Synonym (taxonomy); Word (group theory); Natural language processing; Lexical density; Artificial intelligence; Lexical item","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004213559,0.0002758038,0.0004354458,0.0002070204,0.0001477144,0.0003105039,0.0001852455,0.000416647,0.04957635],"category_scores_gemma":[0.0001891273,0.0002999891,0.00009004173,0.0001802484,0.0002688251,0.0001893169,0.0004205661,0.001114704,0.00006676789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008088147,"about_ca_system_score_gemma":0.00007222977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005741514,"about_ca_topic_score_gemma":0.001034221,"domain_scores_codex":[0.9974763,0.0007077878,0.0004744489,0.0008687582,0.0002117505,0.0002609341],"domain_scores_gemma":[0.9983325,0.0007855329,0.0001489668,0.0004725107,0.00009746302,0.0001630489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0009577465,0.005648284,0.3126498,0.001330572,0.002261652,0.004052113,0.3877883,0.000588052,0.001861795,0.1803747,0.01601949,0.08646753],"study_design_scores_gemma":[0.001260793,0.0000403581,0.9576234,0.001214859,0.00006578045,0.00006739343,0.03422291,0.000366952,0.00002092804,0.003925569,0.00067922,0.0005118329],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714863,0.01592227,0.001464579,0.003842485,0.0005980833,0.0003213623,0.00009174916,0.00009430045,0.006178884],"genre_scores_gemma":[0.9922,0.0001732034,0.001191803,0.00382547,0.0001292945,0.00009756554,0.001060082,0.00002385544,0.001298726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6449736,"threshold_uncertainty_score":0.9999452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05874202672999521,"score_gpt":0.3630260342958163,"score_spread":0.3042840075658211,"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."}}