{"id":"W4411251312","doi":"10.1016/j.infsof.2025.107804","title":"Trust, transparency, and adoption in generative AI for software engineering: Insights from Twitter discourse","year":2025,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transparency (behavior); Generative grammar; Software; Computer science; Business; Knowledge management; Artificial intelligence; Computer security","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.007950091,0.0004270342,0.0003616154,0.001978936,0.005944799,0.00689467,0.0005292214,0.001673346,0.001764773],"category_scores_gemma":[0.02874557,0.0003697352,0.0002446082,0.002308891,0.007000069,0.01064945,0.00458436,0.002212596,0.0003917244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003576069,"about_ca_system_score_gemma":0.001786889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007209286,"about_ca_topic_score_gemma":0.008281715,"domain_scores_codex":[0.9925403,0.005145853,0.0003578099,0.0004417766,0.001099565,0.0004147725],"domain_scores_gemma":[0.9669686,0.02749142,0.002550051,0.0006140973,0.001712978,0.0006629655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001149865,0.00002284456,0.01591455,0.0002949088,0.00001324578,0.0009230386,0.9472983,0.0002215697,0.002791951,0.01260747,0.001686962,0.01811015],"study_design_scores_gemma":[0.00001493748,0.00007866594,0.02467051,0.0006862546,0.00003525857,0.0004885036,0.8865459,0.003602342,0.001979507,0.0104895,0.07131543,0.00009324419],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574887,0.0009057027,0.006414516,0.01359847,0.0001475392,0.00007078036,0.0001993939,0.00005660988,0.02111829],"genre_scores_gemma":[0.9967594,0.0004508384,0.0009278496,0.0006601021,0.00005255467,0.00004356221,0.00006127587,0.0000456099,0.0009989322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9940552,"threshold_uncertainty_score":0.04204464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499657228204741,"score_gpt":0.315984941926942,"score_spread":0.3009883696448946,"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."}}