{"id":"W3215727830","doi":"10.1037/pha0000541","title":"Beyond online participant crowdsourcing: The benefits and opportunities of big team addiction science.","year":2022,"lang":"en","type":"article","venue":"Experimental and Clinical Psychopharmacology","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health","funders":"","keywords":"Crowdsourcing; Addiction; Big data; Grassroots; Intervention (counseling); Population; Citizen science; Empirical research","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07145116,0.0008147322,0.001065908,0.00378141,0.00519753,0.01165916,0.003568177,0.003897456,0.01457187],"category_scores_gemma":[0.1450882,0.0005916652,0.001864256,0.005147681,0.009502322,0.01659368,0.01798503,0.006055291,0.003479833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003544997,"about_ca_system_score_gemma":0.01504613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314892,"about_ca_topic_score_gemma":0.007206959,"domain_scores_codex":[0.9572237,0.03204528,0.001288942,0.002944484,0.005506495,0.0009909933],"domain_scores_gemma":[0.7570426,0.1741606,0.01039083,0.03567819,0.01224106,0.0104868],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003932659,0.0005020798,0.02586301,0.005796005,0.0006795028,0.0005041492,0.02452497,0.002435482,0.001914929,0.2553842,0.1544688,0.5275336],"study_design_scores_gemma":[0.0001649809,0.0003018768,0.011422,0.004531103,0.000156632,0.0001645163,0.01208212,0.003511618,0.001246316,0.52851,0.4377556,0.0001531834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03667696,0.03421161,0.362293,0.3991654,0.01459423,0.004484629,0.007262818,0.002168094,0.1391432],"genre_scores_gemma":[0.4558345,0.03284986,0.367169,0.08172022,0.01280509,0.01651062,0.004150067,0.001309103,0.02765162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9285488,"threshold_uncertainty_score":0.3778744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1027012312634266,"score_gpt":0.3817873964303959,"score_spread":0.2790861651669693,"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."}}