{"id":"W4313563640","doi":"10.1145/3551349.3556917","title":"Automatic Comment Generation via Multi-Pass Deliberation","year":2022,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; Youth Innovation Promotion Association; Chinese Academy of Sciences; National Science Foundation","keywords":"Computer science; Deliberation; Code (set theory); Iterative and incremental development; Process (computing); Python (programming language); Java; Source lines of code; Programming language; Artificial intelligence; Software; Software engineering","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":[0.008423876,0.002811983,0.00191055,0.003447601,0.001348278,0.002693068,0.002891348,0.001972183,0.008005735],"category_scores_gemma":[0.04475166,0.0007102953,0.0022671,0.001838306,0.001187719,0.005187557,0.00529475,0.002378348,0.008489219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103159,"about_ca_system_score_gemma":0.002282677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002400199,"about_ca_topic_score_gemma":0.003229292,"domain_scores_codex":[0.9865679,0.00585027,0.0009493489,0.002843376,0.00326099,0.0005281746],"domain_scores_gemma":[0.9573982,0.02559696,0.002221461,0.005566325,0.008093831,0.001123326],"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":[0.001561663,0.0005101518,0.007126064,0.00201787,0.0002698627,0.0009164126,0.005753885,0.01245887,0.04145517,0.0103731,0.07360107,0.8439559],"study_design_scores_gemma":[0.0005701978,0.0007222801,0.005248913,0.0004600401,0.0003612301,0.0009662047,0.003150908,0.706037,0.0962038,0.05123927,0.1345664,0.0004737529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02311791,0.00063929,0.9173836,0.0008624737,0.0003497956,0.001292471,0.002142911,0.0505283,0.003683271],"genre_scores_gemma":[0.1762702,0.0003975485,0.7941882,0.0005832352,0.0003132262,0.001677652,0.01176054,0.003615032,0.01119435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008423876,"threshold_uncertainty_score":0.04455024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04805307435243965,"score_gpt":0.2612893608342793,"score_spread":0.2132362864818396,"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."}}