{"id":"W2778195513","doi":"10.1017/9781139086264","title":"Direct Objects and Language Acquisition","year":2017,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Learnability; Generative grammar; Linguistics; Object (grammar); Computer science; Transitive relation; Grammar; Language acquisition; Emergent grammar; Reading (process); Artificial intelligence; Natural language processing; Mathematics; Philosophy","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"],"consensus_categories":[],"category_scores_codex":[0.0001083297,0.0002717368,0.0003450782,0.0001459079,0.0006245224,0.0003040914,0.0003001065,0.0001929352,0.00002133293],"category_scores_gemma":[0.00005795434,0.0003175373,0.0001021154,0.000001339399,0.0003557009,0.0001119121,0.0002202939,0.0002195751,0.0000234833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001698187,"about_ca_system_score_gemma":0.0001191308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001609224,"about_ca_topic_score_gemma":0.00012709,"domain_scores_codex":[0.9990252,0.00005109988,0.0001293044,0.0003853277,0.0001975115,0.0002115374],"domain_scores_gemma":[0.9988337,0.00009227498,0.0003131771,0.0004975304,0.0001726093,0.00009067773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003587696,0.000009548525,0.000001337794,0.0001859682,0.0001330197,0.0002374069,0.008193235,1.333301e-7,0.0000161839,0.9565923,0.03420523,0.000389789],"study_design_scores_gemma":[0.0006413832,0.00005516603,0.00004582549,0.0004092954,0.0005329956,0.000006508729,0.001247782,0.00005197252,0.0001876539,0.0001652112,0.9960787,0.0005774484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005079846,0.0001250146,0.00002655573,0.00006681566,0.001006389,0.000291027,0.0005160589,0.0001610711,0.9972991],"genre_scores_gemma":[0.03782556,0.00003054539,0.00002610133,0.0000449634,0.001674552,7.300461e-7,0.0001686698,0.00003991143,0.960189],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9618735,"threshold_uncertainty_score":0.9999277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063084022383187,"score_gpt":0.2062683962852596,"score_spread":0.1856375560614277,"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."}}