{"id":"W3152968659","doi":"10.24908/iqurcp.10467","title":"Learning Nouns and Verbs using Cross-situational Statistics","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Verb; Noun; Linguistics; Word order; Psychology; Natural language processing; Artificial intelligence; Object (grammar); Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001688477,0.0002271665,0.0002441012,0.0005114644,0.001093267,0.001373333,0.000963123,0.0001745365,0.0000169609],"category_scores_gemma":[0.00102951,0.0002256198,0.00003593454,0.0009095823,0.00246755,0.000976768,0.0008491402,0.0009259646,0.0001000902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001610795,"about_ca_system_score_gemma":0.0004725958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001363568,"about_ca_topic_score_gemma":0.000006753613,"domain_scores_codex":[0.9968765,0.00009238474,0.0003340534,0.0008303952,0.0009923643,0.000874331],"domain_scores_gemma":[0.9958228,0.000302463,0.0001439131,0.000225068,0.003287258,0.0002185278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000269416,0.00006165089,0.03889258,0.00006469147,0.00004834381,0.00001778171,0.00207786,0.000005391411,0.008006153,0.9299889,0.00120615,0.0196036],"study_design_scores_gemma":[0.001189883,0.001764547,0.03383671,0.0003177132,0.0000203151,0.0001624789,0.001689766,0.2495508,0.008575797,0.69713,0.004838976,0.0009230608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4415031,0.00003507,0.5517192,0.004186544,0.0001991926,0.0002270383,0.000004480361,0.0003836764,0.001741704],"genre_scores_gemma":[0.9490178,0.0001106244,0.05014013,0.00004526035,0.0002129559,0.00001864262,0.000004047907,0.00002000443,0.000430496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5075148,"threshold_uncertainty_score":0.9996634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.123024030955708,"score_gpt":0.4100912208508778,"score_spread":0.2870671898951698,"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."}}