{"id":"W3194836746","doi":"10.4018/jdm.2018010101","title":"Beyond Micro-Tasks","year":2018,"lang":"en","type":"article","venue":"Journal of Database Management","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Saskatchewan","funders":"","keywords":"Crowdsourcing; Crowds; Data science; Exploit; Computer science; Scope (computer science); Extant taxon; Domain (mathematical analysis); Observational study; Redundancy (engineering); Scale (ratio); Knowledge management; World Wide Web; Computer security; 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":[0.003716714,0.001229421,0.001205748,0.001546265,0.001588367,0.006065037,0.002560691,0.002278399,0.01649395],"category_scores_gemma":[0.02108172,0.0005161689,0.001042669,0.001823488,0.00313976,0.01075549,0.00483314,0.002001694,0.004891954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613192,"about_ca_system_score_gemma":0.002727786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005303127,"about_ca_topic_score_gemma":0.004353424,"domain_scores_codex":[0.994921,0.001954513,0.0002836908,0.001324983,0.00106982,0.0004459206],"domain_scores_gemma":[0.9826896,0.01066175,0.001164182,0.002946913,0.001470173,0.001067325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004432485,0.0003303092,0.01157872,0.003135459,0.0003414817,0.0005229567,0.003168428,0.04224864,0.003028888,0.5597905,0.04583125,0.3295801],"study_design_scores_gemma":[0.00005520094,0.0001276919,0.005438069,0.0004281668,0.00008891583,0.0003218226,0.001815542,0.07752067,0.001328988,0.7585637,0.154237,0.00007424358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05560869,0.02823118,0.6736993,0.02204042,0.001584723,0.001146822,0.00384415,0.00207464,0.2117701],"genre_scores_gemma":[0.7713554,0.01008838,0.170767,0.003357306,0.001665348,0.001118128,0.002950718,0.0005832251,0.03811446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01649395,"threshold_uncertainty_score":0.05517775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260022029478405,"score_gpt":0.2474402637628823,"score_spread":0.2348400434680982,"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."}}