{"id":"W1695056469","doi":"10.5964/bioling.8661","title":"The Asymmetry of Merge","year":2008,"lang":"en","type":"article","venue":"Biolinguistics","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Merge (version control); Computer science; Generative grammar; Grammar; Merge algorithm; Artificial intelligence; Natural language processing; Theoretical computer science; Mathematics; Algorithm; Linguistics; Information retrieval; 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":[0.004059754,0.0004113351,0.000787499,0.001903079,0.00230222,0.004254614,0.001356627,0.001593357,0.009513468],"category_scores_gemma":[0.01467239,0.0005355293,0.001169465,0.001409668,0.008947349,0.02379267,0.008361435,0.002426975,0.001319366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001551588,"about_ca_system_score_gemma":0.001015508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007241264,"about_ca_topic_score_gemma":0.0004878773,"domain_scores_codex":[0.9949759,0.001276236,0.0004044065,0.001080976,0.001674784,0.0005876253],"domain_scores_gemma":[0.9932663,0.002830405,0.0007577244,0.002060469,0.0008766467,0.0002084032],"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":[0.0000521586,0.000004291233,0.0006292573,0.00004379676,0.000007370657,0.00008102123,0.0009647736,0.0002439174,0.001072606,0.9867043,0.0004008485,0.009795686],"study_design_scores_gemma":[0.00001441067,0.00003141737,0.0009379785,0.00003955983,0.00002348537,0.0005360691,0.0006136173,0.001527767,0.003850616,0.9679817,0.02442178,0.00002151789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2336422,0.002299737,0.3833718,0.005294588,0.000426882,0.00009944646,0.0004877964,0.0008609819,0.3735165],"genre_scores_gemma":[0.9723176,0.0005492166,0.0180837,0.0005565975,0.0002151091,0.00007394306,0.0002243601,0.0002675487,0.007711778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009513468,"threshold_uncertainty_score":0.03182572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04035854022898569,"score_gpt":0.2434221813249237,"score_spread":0.203063641095938,"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."}}