{"id":"W2980764660","doi":"10.48550/arxiv.1910.08167","title":"Context-Augmented Software Development Projects: Literature Review and Preliminary Framework","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Context (archaeology); Software development; Software; Reuse; Software engineering; Knowledge management; Software project management; Data science; Package development process; Software construction; 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":[0.002773305,0.001029912,0.001360742,0.01624775,0.0009706144,0.003848023,0.001298453,0.001502576,0.002839646],"category_scores_gemma":[0.01065908,0.0006964367,0.001249877,0.02051628,0.0009639087,0.005032225,0.00173918,0.001106574,0.0005489407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002032558,"about_ca_system_score_gemma":0.005624464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008614847,"about_ca_topic_score_gemma":0.01128426,"domain_scores_codex":[0.9979961,0.000661784,0.0003868501,0.0003657459,0.0004870943,0.0001024287],"domain_scores_gemma":[0.9857305,0.01085401,0.001069696,0.0002724943,0.00183909,0.0002342386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000137747,0.0001308034,0.00590613,0.0966,0.0003822465,0.0004593774,0.002236769,0.001496819,0.0006846584,0.01979772,0.01091161,0.8612561],"study_design_scores_gemma":[0.0000497393,0.0003573855,0.04090507,0.2094491,0.003975435,0.003049075,0.01080731,0.005232238,0.001980239,0.03273936,0.6911879,0.000267081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004011867,0.9837952,0.005189681,0.00139835,0.0002573594,0.0001121108,0.0003303137,0.0000462305,0.004858851],"genre_scores_gemma":[0.04247699,0.9489236,0.00694628,0.0003618745,0.0002530776,0.0001644751,0.0004073618,0.00001134716,0.0004550558],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01624775,"threshold_uncertainty_score":0.01712936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06557561057708045,"score_gpt":0.2035294387344017,"score_spread":0.1379538281573213,"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."}}