{"id":"W1548204199","doi":"10.1007/978-3-642-29863-9_14","title":"What Makes Corporate Wikis Work? Wiki Affordances and Their Suitability for Corporate Knowledge Work","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Affordance; Computer science; Knowledge management; Work (physics); The Internet; Software deployment; Empirical research; Perception; World Wide Web; Human–computer interaction; Engineering; Software engineering; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002737995,0.0004334651,0.0004808954,0.0003026663,0.001015153,0.001204084,0.0008615098,0.0003924109,0.00006243428],"category_scores_gemma":[0.0002659841,0.0003711962,0.00009293146,0.001095426,0.002998782,0.001403959,0.0002033672,0.0003819176,0.00001789827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003822783,"about_ca_system_score_gemma":0.001352813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002399659,"about_ca_topic_score_gemma":0.002445127,"domain_scores_codex":[0.9973296,0.0001257957,0.0004533458,0.0009495011,0.0004554791,0.0006862652],"domain_scores_gemma":[0.9966986,0.001057142,0.0007393254,0.0005293045,0.0007128615,0.0002627208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004320147,0.00006762426,0.002949493,0.00005034256,0.00001264865,7.296507e-7,0.02611622,0.0002300821,0.00001049497,0.03353438,0.0002139873,0.9367708],"study_design_scores_gemma":[0.0004938547,0.0001914035,0.003630537,0.001231336,0.00004205591,0.000003549171,0.0003251372,0.001327822,0.0004406543,0.8177399,0.1729892,0.001584506],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02608452,0.03033314,0.8888448,0.009605483,0.03032935,0.004384042,0.00004499602,0.0003723266,0.01000134],"genre_scores_gemma":[0.9522966,0.001682964,0.03563488,0.0009836697,0.003539674,0.0001260807,0.00003509468,0.00006215853,0.005638887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9351863,"threshold_uncertainty_score":0.999874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05796368102806083,"score_gpt":0.3019167851483116,"score_spread":0.2439531041202507,"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."}}