{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008473283,0.0002759292,0.0002658293,0.0001803071,0.0007821804,0.0006017326,0.0007917284,0.0001392599,0.000239323],"category_scores_gemma":[0.00007140901,0.0002185858,0.0001139926,0.0005784369,0.0001168184,0.0006996284,0.0006161651,0.0002760489,0.00051939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001199755,"about_ca_system_score_gemma":0.0001509327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008468602,"about_ca_topic_score_gemma":0.00005935719,"domain_scores_codex":[0.997522,0.0001724763,0.0003987405,0.0007554943,0.0005470645,0.0006042175],"domain_scores_gemma":[0.9979993,0.0001424014,0.0001565908,0.001223703,0.0002388882,0.0002391234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003378302,0.0005377721,0.02177287,0.0001244372,0.00009911041,0.0000862106,0.005162579,0.0006053394,0.293868,0.04648444,0.0647273,0.5664982],"study_design_scores_gemma":[0.002822131,0.0007923148,0.03981955,0.001362949,0.00007756178,0.0005357257,0.001082882,0.4368072,0.1683679,0.009097453,0.3361655,0.003068865],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1753565,0.00003883416,0.7885414,0.0007193652,0.0008899163,0.0001326485,3.6826e-7,0.0006569467,0.033664],"genre_scores_gemma":[0.7995949,0.000005086134,0.1960006,0.0006839347,0.0003738366,0.000008133816,0.000002599222,0.00002125673,0.003309643],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6242384,"threshold_uncertainty_score":0.8913671,"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."}}