{"id":"W6927454037","doi":"10.26188/28636739.v1","title":"Improving digital citizen science by learning from volunteer practices in biodiversity monitoring","year":2025,"lang":"en","type":"report","venue":"Figshare","topic":"Diphtheria, Corynebacterium, and Tetanus","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citizen science; Data collection; Biodiversity; Public participation; Public engagement; The Internet; Digital preservation; Science education","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001446058,0.0002723538,0.0002528951,0.0001151535,0.0001553159,0.0004361198,0.0006019151,0.0003580954,0.002573646],"category_scores_gemma":[0.006004924,0.0002961642,0.0001063237,0.0001710595,0.00005316712,0.00004190935,0.0008219428,0.0004170356,0.0001350629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001547873,"about_ca_system_score_gemma":0.001211008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005202775,"about_ca_topic_score_gemma":0.00002044982,"domain_scores_codex":[0.9981424,0.00002846604,0.0002301957,0.0007950168,0.0004416561,0.0003622276],"domain_scores_gemma":[0.9985324,0.00004820441,0.0005665796,0.0003682042,0.0003959142,0.0000886899],"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":[0.0001282328,0.0001805102,0.04062653,0.0009628253,0.0002732181,0.0001983328,0.0001980946,0.00001304559,0.264593,9.024969e-8,0.613988,0.07883814],"study_design_scores_gemma":[0.0002678556,0.00007891005,0.004896479,0.001192309,0.00003012031,0.000007347575,0.0001627114,0.00001133926,0.0277066,0.000001240072,0.9651406,0.0005044895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3571467,0.0102871,0.000009108559,0.00005453667,0.002201605,0.0007745891,0.5394086,0.0001471175,0.08997069],"genre_scores_gemma":[0.6646923,0.0002579404,0.00004303603,0.0000359089,0.0009058116,0.00006423694,0.3193832,0.00003697336,0.01458051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3511526,"threshold_uncertainty_score":0.999949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03890610641618249,"score_gpt":0.2855409817291345,"score_spread":0.246634875312952,"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."}}