{"id":"W2765493762","doi":"10.3390/su9112019","title":"Crowdsourcing Analysis of Twitter Data on Climate Change: Paid Workers vs. Volunteers","year":2017,"lang":"en","type":"article","venue":"Sustainability","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Saint Vincent University","funders":"University of Florida","keywords":"Crowdsourcing; Amateur; Data processing; Citizen science; Data science; Social media; Computer science; Climate change; Limiting; World Wide Web; Engineering; Database; Geography","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":[0.002619812,0.0002627368,0.0005687016,0.0003579587,0.000785134,0.0005274913,0.003306982,0.0001176657,0.00001614419],"category_scores_gemma":[0.001652294,0.0002425267,0.0002431257,0.0006619888,0.0003634502,0.0008962848,0.002120919,0.0002717107,0.000007341042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003017868,"about_ca_system_score_gemma":0.0001569012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001603366,"about_ca_topic_score_gemma":0.0001393166,"domain_scores_codex":[0.9970422,0.0002106599,0.0004588522,0.001107729,0.000468125,0.0007124035],"domain_scores_gemma":[0.9905463,0.0002104553,0.000403789,0.008167534,0.0005120517,0.0001599012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001238183,0.0002171261,0.9299265,0.0002950306,0.0004337173,0.00005897099,0.004431515,0.00202118,0.00004743523,0.003392857,0.0008497507,0.05820216],"study_design_scores_gemma":[0.000384407,0.0001182033,0.8265056,0.00008699806,0.0003409929,0.000002092835,0.001177111,0.1683161,0.0002966598,0.001170425,0.001186647,0.0004147466],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960167,0.00004328934,0.0332563,0.004743815,0.0003587701,0.0004320083,0.00002283093,0.0001723883,0.0008036321],"genre_scores_gemma":[0.9982122,0.000005244591,0.001275395,0.0002585753,0.00009355767,0.00001674071,0.00001618694,0.00001591067,0.0001062361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1662949,"threshold_uncertainty_score":0.9889954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05085086884443499,"score_gpt":0.3298584126768211,"score_spread":0.2790075438323861,"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."}}