{"id":"W4399519565","doi":"10.3389/fcomm.2024.1293401","title":"Persian compounds in the mental lexicon","year":2024,"lang":"en","type":"article","venue":"Frontiers in Communication","topic":"Reading and Literacy Development","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Persian; Compound; Lexicon; Transparency (behavior); Natural language processing; Head (geology); Linguistics; Decomposition; Artificial intelligence; Computer science; Chemistry; Biology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002108173,0.0003307482,0.0002032825,0.0006337708,0.000275085,0.002053001,0.0001993781,0.0001653318,0.008024821],"category_scores_gemma":[0.001108183,0.0001666754,0.0001914727,0.0007415278,0.0007789618,0.001681265,0.0005960245,0.0003393883,0.001367225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005722269,"about_ca_system_score_gemma":0.0004220419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917186,"about_ca_topic_score_gemma":0.002998389,"domain_scores_codex":[0.9997887,0.00004767157,0.00002114146,0.00007504012,0.00004725685,0.00002021627],"domain_scores_gemma":[0.9995674,0.0001588323,0.00008184086,0.00008844036,0.0000832001,0.00002028158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007568303,0.0001236804,0.04650951,0.0006884233,0.0001448319,0.002598697,0.02603991,0.0028837,0.1576823,0.2045107,0.008796734,0.5492646],"study_design_scores_gemma":[0.0001518562,0.0005857776,0.3437222,0.0002576867,0.0003131388,0.008220202,0.01628782,0.0250871,0.08751426,0.2525596,0.2650723,0.0002281684],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8753226,0.001595713,0.02279301,0.0005120168,0.00008209792,0.000051126,0.001288256,0.0006840309,0.097671],"genre_scores_gemma":[0.99173,0.0002182029,0.004322048,0.00004425762,0.0000099389,0.0000118333,0.0003887309,0.00005158429,0.003223449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008024821,"threshold_uncertainty_score":0.02684569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02345744467885373,"score_gpt":0.324864299623464,"score_spread":0.3014068549446102,"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."}}