{"id":"W2893414612","doi":"10.1145/3258692","title":"Session details: Session 7A: Crowdsourcing & Assessment","year":2018,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Session (web analytics); Crowdsourcing; Computer science; Multimedia; World Wide Web","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01033307,0.001859936,0.001670039,0.002109114,0.003770483,0.007187201,0.002809383,0.004083717,0.474317],"category_scores_gemma":[0.02473874,0.0004778022,0.002254166,0.001124313,0.0007371258,0.00309948,0.006984838,0.003752646,0.3141761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002914381,"about_ca_system_score_gemma":0.007587557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007583357,"about_ca_topic_score_gemma":0.01551052,"domain_scores_codex":[0.9943106,0.001035003,0.0001833581,0.000568916,0.003044896,0.0008571774],"domain_scores_gemma":[0.9619384,0.003201311,0.0005669109,0.002441558,0.02341907,0.008432634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001047997,0.0005477418,0.0007745528,0.0004440004,0.00004688924,0.00004122673,0.00008973516,0.0005125451,0.0009900514,0.0009067304,0.9426569,0.05194143],"study_design_scores_gemma":[0.0005144595,0.001436122,0.008851832,0.0005748456,0.00008731239,0.00006410411,0.0005530055,0.001715228,0.003495638,0.006135725,0.9764668,0.000104858],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01830935,0.00272582,0.02738125,0.03121322,0.05680095,0.02567399,0.08981503,0.01125861,0.7368219],"genre_scores_gemma":[0.07782522,0.002045646,0.0162351,0.006625383,0.007435754,0.01303848,0.0579721,0.003251713,0.8155707],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5256829,"threshold_uncertainty_score":0.7498229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375889438937933,"score_gpt":0.2999242211704743,"score_spread":0.276165326781095,"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."}}