{"id":"W3145226536","doi":"10.1145/3362741","title":"Help Me to Help You","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Social Computing","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Los Alamos National Laboratory; Science and Technology Facilities Council; Planetary Science Division; Science Mission Directorate; Smithsonian Astrophysical Observatory; Max-Planck-Institut für Astronomie; Queen's University; University of Edinburgh; Johns Hopkins University; Queen's University Belfast; National Aeronautics and Space Administration; Eötvös Loránd Tudományegyetem; National Central University; Central Laser Facility, Science and Technology Facilities Council; Space Telescope Science Institute; Durham University; Smithsonian Institution; National Science Foundation","keywords":"Citizen science; Leverage (statistics); MNIST database; Software deployment; Computer science; Competition (biology); Data science; Variety (cybernetics); Artificial intelligence; Machine learning; Deep learning; Software engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001072804,0.001206567,0.0006768694,0.001029158,0.003298052,0.004138755,0.001121139,0.002231807,0.4815901],"category_scores_gemma":[0.01367369,0.0003023519,0.0006166156,0.0006384358,0.0008071036,0.004760493,0.004598168,0.002583945,0.4347056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006169513,"about_ca_system_score_gemma":0.001450618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001507884,"about_ca_topic_score_gemma":0.00356018,"domain_scores_codex":[0.9989824,0.0002558712,0.00003375073,0.0001920955,0.0003274212,0.0002085281],"domain_scores_gemma":[0.9943264,0.000464061,0.0002493976,0.0003690392,0.001680079,0.00291102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001762185,0.00003182976,0.0005164375,0.00006600546,0.000003601901,0.0001113395,0.0004841017,0.00001108563,0.000107446,0.0007623743,0.9567047,0.0411834],"study_design_scores_gemma":[0.000006920854,0.00002274736,0.0004063711,0.0001054619,0.000004718928,0.0004448718,0.001354497,0.00003866546,0.00009629979,0.0008022748,0.9967044,0.00001280694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01521673,0.01045927,0.01714161,0.2217862,0.04658584,0.0008455911,0.007363482,0.01482484,0.6657764],"genre_scores_gemma":[0.0296756,0.004014555,0.008553145,0.06706259,0.002996272,0.0004050704,0.002691844,0.001851091,0.8827498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4815901,"threshold_uncertainty_score":0.7394488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03797441798776483,"score_gpt":0.2828596139350032,"score_spread":0.2448851959472384,"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."}}