{"id":"W4240736797","doi":"10.1109/icse.2005.1553554","title":"Using structural context to recommend source code examples","year":2005,"lang":"en","type":"article","venue":"Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005.","topic":"Software Engineering Research","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Programming language; Source code; Eclipse; Coding (social sciences); Code (set theory); Context (archaeology); Code review; Class (philosophy); Task (project management); Software engineering; Static program analysis; Artificial intelligence; Software development; Software","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":[0.001366863,0.0009236082,0.0007492832,0.01162717,0.0008760439,0.00139657,0.001210816,0.001606331,0.002587083],"category_scores_gemma":[0.02000114,0.0006529509,0.0006026751,0.004178875,0.0004222589,0.002411387,0.001040107,0.001022662,0.001319806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006280293,"about_ca_system_score_gemma":0.00157684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009186104,"about_ca_topic_score_gemma":0.03188726,"domain_scores_codex":[0.998519,0.0003348355,0.0001205452,0.0003876174,0.0005604683,0.00007740232],"domain_scores_gemma":[0.9872869,0.007771716,0.0008959124,0.0008917568,0.00282727,0.0003264352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007326397,0.0007410059,0.1246018,0.001276469,0.0002659054,0.001161008,0.002439795,0.02147619,0.01625875,0.00435651,0.02939801,0.7972919],"study_design_scores_gemma":[0.0004125845,0.0007061492,0.06686115,0.0008933516,0.0007244013,0.002291388,0.002704463,0.807664,0.02999835,0.02334597,0.06413507,0.0002631363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5314711,0.003857446,0.4343197,0.001336672,0.0002030036,0.0009903619,0.004720969,0.01196968,0.01113095],"genre_scores_gemma":[0.6418262,0.0009470137,0.3447293,0.0001907325,0.00008863647,0.0004611115,0.008907407,0.0005992816,0.002250393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01162717,"threshold_uncertainty_score":0.01826525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06840004737661666,"score_gpt":0.3165482477123839,"score_spread":0.2481482003357673,"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."}}