{"id":"W2128243924","doi":"10.1111/j.1083-6101.2007.00344.x","title":"Shake, Rattle, and Roles: Lessons from Experimental Earthquake Engineering for Incorporating Remote Users in Large-Scale E-Science Experiments","year":2007,"lang":"en","type":"article","venue":"Journal of Computer-Mediated Communication","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"U.S. Department of Defense","keywords":"Cyberinfrastructure; Exploit; Citizen science; Scale (ratio); Shake; Computer science; Crowdsourcing; Point (geometry); Data science; Computer security; Engineering; Remote sensing; World Wide Web; Geography","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":[0.02323013,0.0007340239,0.0005529523,0.0006568331,0.00588398,0.003674118,0.003548062,0.003685163,0.00580292],"category_scores_gemma":[0.04235165,0.0006095678,0.0005706613,0.0004840733,0.01400068,0.008178312,0.00494296,0.003695422,0.000871281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002110655,"about_ca_system_score_gemma":0.002814217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805292,"about_ca_topic_score_gemma":0.006357552,"domain_scores_codex":[0.9838975,0.01435831,0.0001676608,0.0004998773,0.0005357027,0.0005410499],"domain_scores_gemma":[0.9576072,0.03594683,0.0008641928,0.00299642,0.001047307,0.001538164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001354082,0.006847768,0.02925039,0.00181178,0.0001244832,0.003544061,0.5246472,0.01070269,0.01304967,0.1939497,0.01057702,0.2041412],"study_design_scores_gemma":[0.001047916,0.004094132,0.01943492,0.001244462,0.0001051845,0.001564621,0.3056767,0.01863135,0.008711376,0.4842851,0.1548749,0.0003292529],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.74447,0.00164407,0.1046321,0.03589053,0.0004314697,0.001888759,0.0001233728,0.0002720191,0.1106478],"genre_scores_gemma":[0.9641655,0.0007590701,0.02907206,0.001196737,0.00004102469,0.000999609,0.00003630384,0.00006439212,0.003665305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02323013,"threshold_uncertainty_score":0.1228542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715442571972349,"score_gpt":0.2818247318407464,"score_spread":0.2646703061210229,"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."}}