{"id":"W7117136245","doi":"10.23641/asha.30888404.v1","title":"Interactive features and language trajectories (Sylvestre et al., 2025)","year":2025,"lang":"","type":"other","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Utterance; Neglect; Normative; Mean length of utterance; Language development; Longitudinal study; Quality (philosophy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006079629,0.0002136945,0.0001028884,0.001091975,0.0008088367,0.001417567,0.0003030214,0.000274512,0.007063816],"category_scores_gemma":[0.002915775,0.0001287863,0.0002112501,0.0007406072,0.0006984663,0.0007463866,0.0009718076,0.0004575045,0.0007458168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440493,"about_ca_system_score_gemma":0.001914921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07722195,"about_ca_topic_score_gemma":0.1595325,"domain_scores_codex":[0.9997312,0.00005753683,0.00001555051,0.00004295248,0.00008875407,0.0000639718],"domain_scores_gemma":[0.9986728,0.000195155,0.0004193008,0.00007576026,0.0003374702,0.0002994865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008238393,0.00006183414,0.9312704,0.00004258058,0.00002877146,0.0006522207,0.008678927,0.0001623238,0.001329232,0.001843312,0.001565965,0.05428206],"study_design_scores_gemma":[0.000001178751,0.00002636469,0.9934743,0.00002798102,0.000005295879,0.0004761216,0.0025857,0.00006766446,0.0001495643,0.0003034547,0.002876963,0.000005334402],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9831396,0.0009460947,0.0005117357,0.0006895757,0.00001106037,0.0000244797,0.0008844526,0.00002740386,0.01376562],"genre_scores_gemma":[0.9938402,0.0006166686,0.0007869418,0.00005639932,0.000004646944,0.0000347935,0.0006825561,0.00001187333,0.003966094],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.07722195,"threshold_uncertainty_score":0.153545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01620487659292094,"score_gpt":0.3504794802865092,"score_spread":0.3342746036935882,"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."}}