{"id":"W4400314457","doi":"10.2196/50240","title":"The Impact of Incentives on Data Collection for Online Surveys: Social Media Recruitment Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"RTI International","keywords":"Incentive; Data collection; Social media; Advertising; Survey data collection; Business; Quality (philosophy); Data quality; Incentive program; Marketing; Computer science; Economics; World Wide Web; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1822915,0.0007726122,0.0007274419,0.001252927,0.003877121,0.004253773,0.002548835,0.002698031,0.006340501],"category_scores_gemma":[0.3914838,0.001229141,0.001310617,0.001302448,0.003682261,0.005051936,0.003839579,0.002827663,0.001044826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004710981,"about_ca_system_score_gemma":0.01028505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00239726,"about_ca_topic_score_gemma":0.003172879,"domain_scores_codex":[0.7378065,0.2241131,0.00883563,0.006326973,0.01829602,0.00462185],"domain_scores_gemma":[0.3532676,0.5440745,0.0494769,0.02796209,0.01608634,0.009132602],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03134819,0.206226,0.3889445,0.002470372,0.0008922375,0.0005566364,0.04791008,0.002636326,0.005749204,0.01039472,0.009660835,0.2932111],"study_design_scores_gemma":[0.0212589,0.1770053,0.681376,0.002395473,0.001626545,0.0008053866,0.02947148,0.02294548,0.01322421,0.01003366,0.03907169,0.0007857899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725119,0.0001371907,0.006501045,0.001505132,0.0001461515,0.01093149,0.0001877441,0.00007696856,0.008002223],"genre_scores_gemma":[0.9582485,0.0001225116,0.01841718,0.00222305,0.0001709243,0.01940344,0.000107769,0.00005329611,0.001253312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8177085,"threshold_uncertainty_score":0.964061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7987813230260004,"score_gpt":0.6803447426956319,"score_spread":0.1184365803303684,"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."}}