{"id":"W1044159086","doi":"10.1007/978-3-662-43936-4_11","title":"Design Patterns for Multiple Stakeholders in Social Computing","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Access Control and Trust","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Stakeholder; Focus (optics); Control (management); Work (physics); Scheme (mathematics); Access control; Data science; Computer security; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002179851,0.0003258671,0.0005035492,0.0004469444,0.0008857035,0.0003636188,0.001283219,0.0003734166,0.00002498516],"category_scores_gemma":[0.0002890194,0.0003207683,0.0001229004,0.0002628322,0.0008190481,0.0001958672,0.0002184489,0.0005006269,0.00000756763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003493448,"about_ca_system_score_gemma":0.0004935818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006153715,"about_ca_topic_score_gemma":0.004815122,"domain_scores_codex":[0.9971082,0.000105846,0.0004214675,0.0008567274,0.0006991624,0.0008086555],"domain_scores_gemma":[0.9974252,0.001784785,0.0002677646,0.0002426201,0.0001702914,0.0001093229],"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":[0.00002606967,0.00002165512,0.00176558,0.00004026602,0.00000956554,0.0000146496,0.008240722,0.02020908,0.00001220192,0.01099368,0.00003479658,0.9586318],"study_design_scores_gemma":[0.003638345,0.0003083858,0.003710178,0.0008771739,0.00004309697,0.000004179161,0.00003622677,0.7696393,0.0001639702,0.2051971,0.01404086,0.00234114],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003494873,0.00006496083,0.9948468,0.0008760801,0.001008702,0.0008751961,0.000009385379,0.00007077248,0.001898648],"genre_scores_gemma":[0.9631126,0.000009089676,0.03399954,0.0008996128,0.001733889,0.00001383905,0.000005957704,0.00003187741,0.0001935903],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9627631,"threshold_uncertainty_score":0.9999244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09177807539820083,"score_gpt":0.3079842239667986,"score_spread":0.2162061485685978,"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."}}