{"id":"W1983225447","doi":"10.1177/154193120905300432","title":"Work Domain Analysis for Establishing Collaborative Work Requirements","year":2009,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; University of Waterloo","funders":"","keywords":"Domain (mathematical analysis); Work (physics); Task (project management); Context (archaeology); Computer science; Knowledge management; Process management; Engineering; Systems 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007088638,0.0002011746,0.0003618514,0.0000823261,0.0007596624,0.000180122,0.0002888013,0.0001449189,0.00005693538],"category_scores_gemma":[0.000100553,0.0001657367,0.0003936034,0.0007154754,0.0001040461,0.000396622,0.00007312984,0.000206387,0.000001241883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057473,"about_ca_system_score_gemma":0.00001342709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002046652,"about_ca_topic_score_gemma":0.00000449255,"domain_scores_codex":[0.9986591,0.00001874942,0.0005264769,0.0003518245,0.000142469,0.0003013841],"domain_scores_gemma":[0.9986661,0.0001503213,0.0006480291,0.0001108008,0.0003482817,0.00007646241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006238307,0.0003471497,0.5726375,0.00008495768,0.002775153,1.049985e-7,0.3325739,0.000209154,0.002735746,0.04142018,0.04479909,0.001793203],"study_design_scores_gemma":[0.001221333,0.0001762663,0.8543804,0.0001856794,0.0004742225,4.876347e-7,0.1307261,0.00007128299,0.0008967243,0.003000818,0.008350328,0.0005162918],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944705,0.00006164989,0.0001023262,0.0003438758,0.0002791986,0.0003324304,0.00004474185,0.00005547891,0.004309764],"genre_scores_gemma":[0.996958,0.000008010985,0.001835171,0.0002614659,0.0001400378,0.00002050319,0.00001211414,0.00001590639,0.0007488001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2817429,"threshold_uncertainty_score":0.6758547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753060863111575,"score_gpt":0.3152281566097626,"score_spread":0.2876975479786468,"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."}}