{"id":"W4252966483","doi":"10.1007/s10664-021-10000-w","title":"FACER: An API usage-based code-example recommender for opportunistic reuse","year":2021,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Snippet; Java; Application programming interface; Code reuse; Android (operating system); Source code; Cluster analysis; Reuse; Information retrieval; Code (set theory); Software; World Wide Web; Data mining; Programming language; Operating system; Artificial intelligence; Set (abstract data type)","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":[0.001238903,0.0008834961,0.0009414186,0.002319406,0.0006383525,0.0009772158,0.001848028,0.001501087,0.006233498],"category_scores_gemma":[0.0104146,0.0004253397,0.0007600199,0.001439831,0.0002095652,0.002780023,0.001493333,0.001113285,0.004971926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004799229,"about_ca_system_score_gemma":0.0009638646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120767,"about_ca_topic_score_gemma":0.0510541,"domain_scores_codex":[0.9985934,0.0003388387,0.00007796582,0.0002626553,0.0006376084,0.00008959308],"domain_scores_gemma":[0.9948524,0.002071733,0.0002481891,0.001528578,0.001015538,0.0002835189],"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":[0.0009704362,0.001717135,0.04382422,0.0007863286,0.0004010403,0.0006086559,0.000629555,0.01108108,0.01519718,0.004112335,0.1322187,0.7884534],"study_design_scores_gemma":[0.0003086102,0.0007979674,0.02396185,0.0001609682,0.0003165022,0.0013117,0.000539704,0.846889,0.0185285,0.00879581,0.09814468,0.0002447849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3236381,0.00313779,0.5106342,0.001684544,0.000417223,0.0008736973,0.01286581,0.1135965,0.03315217],"genre_scores_gemma":[0.5310368,0.0006631736,0.415424,0.0006895961,0.0001054719,0.0003611962,0.01875448,0.001911475,0.03105375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0120767,"threshold_uncertainty_score":0.0240128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114604003354212,"score_gpt":0.3362907313551917,"score_spread":0.2248303310197705,"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."}}