{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05082768,0.0004633903,0.0004084083,0.001353748,0.005865806,0.01155893,0.002535524,0.002638761,0.006201683],"category_scores_gemma":[0.05229573,0.0004323081,0.0006734648,0.001614821,0.007030286,0.01433121,0.01895655,0.003635398,0.001889705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003583628,"about_ca_system_score_gemma":0.01227108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002888584,"about_ca_topic_score_gemma":0.008098598,"domain_scores_codex":[0.9523991,0.03982038,0.0009429621,0.001706831,0.002836153,0.002294745],"domain_scores_gemma":[0.9495416,0.03043115,0.003572079,0.005371262,0.00453161,0.006552289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001359555,0.001298597,0.01960547,0.001832977,0.00004560945,0.0003656613,0.2472269,0.000878553,0.001489767,0.03099744,0.04197724,0.6541458],"study_design_scores_gemma":[0.0001084284,0.001190701,0.01755749,0.004657754,0.00007929766,0.0004513105,0.2420937,0.002568138,0.002410087,0.07886511,0.6499092,0.0001087745],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3717559,0.006494101,0.1176972,0.2264182,0.001864233,0.004054324,0.0003147026,0.001056165,0.270345],"genre_scores_gemma":[0.8541013,0.007646678,0.104211,0.01328031,0.0006148449,0.002776057,0.0003530027,0.0002050403,0.01681172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05082768,"threshold_uncertainty_score":0.2688057,"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."}}