{"id":"W3095662607","doi":"10.1109/icsme46990.2020.00058","title":"On the Impact of Multi-language Development in Machine Learning Frameworks","year":2020,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Process (computing); Machine learning; Software engineering; Software development; Language acquisition; Software development process; Natural language processing; Programming language; Software; Mathematics education","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":[],"consensus_categories":[],"category_scores_codex":[0.0002461993,0.00006750442,0.00007956557,0.00005645131,0.00002152847,0.00002969592,0.0005290495,0.00004412053,0.00009214308],"category_scores_gemma":[0.001560242,0.00003964096,0.00002924946,0.0004148211,0.00000965438,0.00004751595,0.0001983065,0.0005687348,0.00003932981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004400312,"about_ca_system_score_gemma":0.00005253223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001160834,"about_ca_topic_score_gemma":0.000004874512,"domain_scores_codex":[0.9993603,0.00004132159,0.0001063152,0.0001413486,0.0001896692,0.000161065],"domain_scores_gemma":[0.9989446,0.0007946625,0.00001740265,0.0001709985,0.00001719752,0.00005513817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004167591,0.0002976684,0.3425631,0.00005693709,0.0001046758,0.0001266894,0.06254614,0.4322013,0.005044419,0.007056323,0.0008193717,0.1491417],"study_design_scores_gemma":[0.0001745093,0.00008882934,0.1119213,0.00002143144,1.688728e-7,7.212244e-7,0.00003487222,0.8842032,0.00343875,0.00001581955,0.00002609096,0.00007433091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5204958,0.00004954406,0.478793,0.0004210135,0.00001192385,0.00007075663,1.437616e-7,0.00008623666,0.0000715454],"genre_scores_gemma":[0.9661342,0.000001214749,0.03369846,0.000103153,0.000005808481,0.00000485894,4.284295e-7,0.000005397319,0.00004649769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4520019,"threshold_uncertainty_score":0.2470901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02705651684839476,"score_gpt":0.3046013675790187,"score_spread":0.277544850730624,"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."}}