{"id":"W2102147011","doi":"10.1145/2635868.2635877","title":"Selection and presentation practices for code example summarization","year":2014,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Automatic summarization; Computer science; Presentation (obstetrics); Code (set theory); Selection (genetic algorithm); Source code; Code review; Think aloud protocol; Information retrieval; Software; Natural language processing; Artificial intelligence; Static program analysis; Software development; Programming language; Human–computer interaction; Usability; Set (abstract data type)","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":[0.02780811,0.0008950965,0.0005683099,0.005428843,0.002191007,0.003978119,0.001585462,0.001439619,0.003973257],"category_scores_gemma":[0.161294,0.0005540737,0.0006138921,0.004073152,0.001657363,0.00674538,0.00460001,0.001359085,0.002065922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089815,"about_ca_system_score_gemma":0.001559238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000549672,"about_ca_topic_score_gemma":0.0009385761,"domain_scores_codex":[0.957831,0.02980748,0.003534456,0.003175547,0.004903181,0.0007483781],"domain_scores_gemma":[0.8375285,0.1045746,0.01312148,0.02380869,0.01938329,0.001583364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006251672,0.0003843698,0.02348746,0.003201367,0.0001232379,0.000967639,0.1881907,0.001367949,0.06819291,0.01329162,0.01333725,0.6868303],"study_design_scores_gemma":[0.0003320019,0.002845112,0.06240544,0.006076129,0.0006271758,0.00644663,0.1669538,0.03280802,0.128109,0.06196559,0.5306218,0.0008094492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3088494,0.002297174,0.6501399,0.005122387,0.0003406886,0.003299717,0.0009733695,0.007093435,0.02188391],"genre_scores_gemma":[0.5769993,0.001171391,0.4116205,0.0005922572,0.0002107542,0.002379001,0.001161286,0.001034312,0.004831245],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02780811,"threshold_uncertainty_score":0.1470651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04724173993157055,"score_gpt":0.3281944050403541,"score_spread":0.2809526651087836,"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."}}