{"id":"W2533520058","doi":"10.1145/2989225.2989235","title":"Efficiently implementing the copy semantics of MATLAB's arrays in JavaScript","year":2016,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"JavaScript; Computer science; Programming language; MATLAB; Leverage (statistics); Semantics (computer science); Code (set theory); Operating system; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00136145,0.0009468979,0.0006326401,0.0004556465,0.0005138891,0.003138223,0.002136452,0.0008460032,0.008978472],"category_scores_gemma":[0.01025659,0.0007813381,0.0009043985,0.0006483578,0.001302297,0.004615023,0.001918868,0.002141869,0.006857157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008128986,"about_ca_system_score_gemma":0.001397298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001489309,"about_ca_topic_score_gemma":0.002341793,"domain_scores_codex":[0.9983919,0.0003030046,0.0001722262,0.000327748,0.0006495225,0.0001555456],"domain_scores_gemma":[0.9950982,0.001990054,0.0002479425,0.001765248,0.0007735288,0.000125032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001540259,0.0002642313,0.005070062,0.001215332,0.0001531616,0.001480726,0.002088106,0.04127027,0.107751,0.2277687,0.09845169,0.5129465],"study_design_scores_gemma":[0.0002715507,0.0001848979,0.001158859,0.0003840868,0.00009328371,0.001029918,0.0003424408,0.2704566,0.2604797,0.1989918,0.2663989,0.0002078742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00782619,0.000136705,0.9100937,0.0004234706,0.0001586276,0.00005076711,0.00043436,0.07155048,0.009325719],"genre_scores_gemma":[0.2454628,0.0004867794,0.6886123,0.001200353,0.000161028,0.0002589055,0.001963605,0.04524636,0.016608],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008978472,"threshold_uncertainty_score":0.03003603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014213298486051,"score_gpt":0.2553959548548673,"score_spread":0.2411826563688163,"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."}}