{"id":"W4415389009","doi":"10.1016/j.dib.2025.112203","title":"Plastic Pirates Nova Scotia 2024 dataset - citizen science investigation of anthropogenic litter pollution of aquatic environments","year":2025,"lang":"en","type":"article","venue":"Data in Brief","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Ocean Frontier Institute; Bundesministerium für Bildung und Forschung; Dalhousie University; Christian-Albrechts-Universität zu Kiel","keywords":"Litter; Citizen science; Nova scotia; Marine debris; Plastic pollution; Pollution; Sampling (signal processing); Aquatic ecosystem","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006043881,0.0001232237,0.0001715675,0.0001754976,0.00005913945,0.00002143927,0.0006821278,0.00005369994,0.0008011796],"category_scores_gemma":[0.0004885265,0.000121649,0.00001349731,0.0008187427,0.001455311,0.0004520169,0.0007554821,0.0001000556,0.0001505796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001273528,"about_ca_system_score_gemma":0.0000802573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002920258,"about_ca_topic_score_gemma":0.0006469411,"domain_scores_codex":[0.9984683,0.000049479,0.000442752,0.0004463591,0.0003534963,0.0002396344],"domain_scores_gemma":[0.9989053,0.0001536596,0.0001707851,0.0007105604,0.000002858946,0.00005680889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005319464,0.0001573571,0.308989,0.00008064938,0.00002174978,0.000003349896,0.0001211584,0.00160236,0.6646152,0.0003105362,0.02236804,0.001677352],"study_design_scores_gemma":[0.0007253636,0.00009115945,0.9093159,0.0002467632,0.00007152657,0.000003593689,0.00003858474,0.02644003,0.05843429,0.000814718,0.003594081,0.0002240149],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832853,0.00007175811,0.008574262,0.0001082365,0.0004689489,0.0002136168,0.007049887,0.000004840825,0.0002231702],"genre_scores_gemma":[0.9967687,0.00002378333,0.0009101799,0.00009591317,0.00001053946,0.000001238587,0.00214778,0.0000051372,0.00003677128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6061809,"threshold_uncertainty_score":0.8772355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0211556543788257,"score_gpt":0.2646593028975489,"score_spread":0.2435036485187232,"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."}}