{"id":"W4287773619","doi":"10.5281/zenodo.3748768","title":"Order in Chaos: Prioritizing Mobile App Reviews using Consensus Algorithms","year":2020,"lang":"en","type":"paratext","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"CHAOS (operating system); Computer science; Order (exchange); Algorithm; Consensus algorithm; Data mining; Artificial intelligence; Computer security","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":[0.01088218,0.001797275,0.002926572,0.003546507,0.001952128,0.003250489,0.002644162,0.002171206,0.009369083],"category_scores_gemma":[0.04811017,0.001442354,0.002087058,0.002597851,0.001203156,0.003723863,0.00374423,0.002245926,0.002872798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753492,"about_ca_system_score_gemma":0.005810298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006212178,"about_ca_topic_score_gemma":0.006847383,"domain_scores_codex":[0.9914401,0.003942792,0.0006198905,0.001258508,0.002224739,0.0005140032],"domain_scores_gemma":[0.9620161,0.02512023,0.001499544,0.003137993,0.007119054,0.001107089],"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":[0.0008853768,0.0003158019,0.003363543,0.0006097992,0.0004366763,0.0002516742,0.001271006,0.3685262,0.007344138,0.05809471,0.02233208,0.536569],"study_design_scores_gemma":[0.0001489046,0.0001891661,0.0002669229,0.00004261531,0.00007006298,0.00005080868,0.0001749555,0.9235077,0.003264805,0.06740643,0.004832241,0.00004538765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006562972,0.0001293203,0.9890552,0.0003169189,0.00009117564,0.0004313039,0.0001379172,0.001609589,0.001665612],"genre_scores_gemma":[0.1344241,0.0001361719,0.8573813,0.0002101336,0.0001377775,0.001137213,0.0004953683,0.0005786126,0.005499247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01088218,"threshold_uncertainty_score":0.05755121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08106516786073853,"score_gpt":0.3028904543558362,"score_spread":0.2218252864950977,"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."}}