{"id":"W2042140705","doi":"10.1145/1984701.1984702","title":"Leveraging social media to gather user feedback for software development","year":2011,"lang":"en","type":"article","venue":"","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Social media; Software deployment; Computer science; Transparency (behavior); Software; World Wide Web; Service (business); Social computing; Internet privacy; Multimedia; Business; Software engineering; Computer security; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002479938,0.0001125406,0.0001309041,0.00006862295,0.0001988218,0.0000744641,0.0005387258,0.0000524497,0.00005551776],"category_scores_gemma":[0.00003976945,0.00009262945,0.00004722666,0.0001346529,0.000009238438,0.0001452759,0.0001530694,0.00003996602,0.0002693916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005162419,"about_ca_system_score_gemma":0.00007014823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002733877,"about_ca_topic_score_gemma":0.00003521361,"domain_scores_codex":[0.9990226,0.00001723869,0.0001818006,0.0002951749,0.0001800952,0.000303094],"domain_scores_gemma":[0.9995392,0.0000696287,0.00003620424,0.0001901157,0.00006856045,0.00009629078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002535663,0.0001693677,0.007108134,0.00006005506,0.00009101278,0.00001059119,0.5921506,0.000004008328,0.0008205303,0.04710207,0.1611353,0.1913229],"study_design_scores_gemma":[0.002406922,0.0001700151,0.06238505,0.000200503,0.00001343544,0.000029738,0.004597943,0.001119288,0.07145504,0.005349833,0.8499656,0.002306585],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02696283,0.0000139177,0.968033,0.0003034592,0.0008251414,0.0001887988,6.391411e-7,0.0002822625,0.003389968],"genre_scores_gemma":[0.3470135,2.024481e-7,0.6473068,0.0007827325,0.0002036295,0.00008396617,0.000001334912,0.00001654316,0.00459131],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6888304,"threshold_uncertainty_score":0.3777319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09079557844140053,"score_gpt":0.2559788865886624,"score_spread":0.1651833081472618,"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."}}