{"id":"W2409446443","doi":"10.1017/iop.2015.24","title":"Don't Throw the Baby Out With the Bathwater: Comparing Data Quality of Crowdsourcing, Online Panels, and Student Samples","year":2015,"lang":"en","type":"article","venue":"Industrial and Organizational Psychology","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Crowdsourcing; Legitimacy; Sampling (signal processing); Quality (philosophy); Psychology; Sample (material); Sociology; Computer science; Social psychology; Epistemology; Political science; Law; World Wide Web; Philosophy","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":[0.001132113,0.0001380159,0.000237303,0.00003585906,0.0002248197,0.0001487751,0.0008680764,0.0000937816,0.000007664973],"category_scores_gemma":[0.0001918186,0.00007364358,0.00001118955,0.0002472254,0.0003523421,0.000148031,0.0006400687,0.0002424704,0.00000164375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000010369,"about_ca_system_score_gemma":0.00009329335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000185065,"about_ca_topic_score_gemma":0.0002946114,"domain_scores_codex":[0.9985141,0.0002877674,0.0003054672,0.0004166232,0.0002983785,0.0001777258],"domain_scores_gemma":[0.9985088,0.0003166242,0.0001919386,0.000732685,0.0001682203,0.00008177287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000173444,0.0004368211,0.9227993,0.00001872458,0.0002709767,0.000009048483,0.0171226,0.0006642991,0.001777513,0.02036345,0.01856104,0.01780273],"study_design_scores_gemma":[0.01025039,0.0008263902,0.8980165,0.00013607,0.0001596475,0.0005109148,0.009178277,0.005585529,0.001211962,0.004481615,0.06868338,0.0009592935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9491879,0.0002070161,0.0369877,0.0128298,0.0003855265,0.0001784711,0.00003301949,0.00004160293,0.0001489604],"genre_scores_gemma":[0.9979431,0.00001397625,0.0008461826,0.0007070586,0.0003748525,0.000001344548,0.00004598844,0.0000101448,0.0000573506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05012234,"threshold_uncertainty_score":0.3003098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2956586616495665,"score_gpt":0.3702693215335167,"score_spread":0.07461065988395021,"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."}}