{"id":"W2055699460","doi":"10.1145/2702123.2702508","title":"We Are Dynamo","year":2015,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":274,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Science Foundation","keywords":"Collective action; Affordance; Action (physics); Public relations; Publics; Focus (optics); Political science; Sociology; Computer science; Internet privacy; Human–computer interaction; Physics; Law; Politics","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":[0.000172514,0.00006080925,0.00007127113,0.00003612451,0.00004361573,0.0001358622,0.0003163113,0.00002710428,0.000008235831],"category_scores_gemma":[0.00003169382,0.00004934682,0.00002513682,0.0001622399,0.0000151672,0.0001698298,0.0001245964,0.0000542131,0.0002951694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002299367,"about_ca_system_score_gemma":0.00003563832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002382779,"about_ca_topic_score_gemma":0.00001320329,"domain_scores_codex":[0.9994058,0.00002215202,0.00007853362,0.0001805532,0.0001558593,0.0001571144],"domain_scores_gemma":[0.999362,0.00001948718,0.00002904001,0.0004012336,0.0000529281,0.0001353165],"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":[0.000008600489,0.0001732247,0.007243099,0.00003159909,0.00003249633,0.0002566873,0.007645456,0.002223155,0.001053493,0.2982202,0.3282739,0.3548381],"study_design_scores_gemma":[0.001195139,0.0001751142,0.002097394,0.0001128215,0.00000860575,0.0002625681,0.002508515,0.6200747,0.008269422,0.03228652,0.3321415,0.000867643],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02794665,0.0001885314,0.8800483,0.005406352,0.0005912966,0.00005150461,1.910002e-7,0.000578375,0.08518881],"genre_scores_gemma":[0.9660292,0.00000205386,0.02766781,0.0004373589,0.00005886002,0.000001631499,1.777903e-7,0.000004333194,0.005798589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9380825,"threshold_uncertainty_score":0.3793904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03379351875373135,"score_gpt":0.2387016906852385,"score_spread":0.2049081719315071,"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."}}