{"id":"W6950404534","doi":"10.5281/zenodo.6609321","title":"pydarm","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Calibration; Detector; Noise (video); Mathematical model","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":[],"consensus_categories":[],"category_scores_codex":[0.001175508,0.002280165,0.001496384,0.001334258,0.0009078701,0.002059336,0.004053237,0.00221174,0.2066412],"category_scores_gemma":[0.003367998,0.001516706,0.002647822,0.001419607,0.0003637529,0.00263499,0.001667073,0.00277447,0.1232815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073874,"about_ca_system_score_gemma":0.001663052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01127038,"about_ca_topic_score_gemma":0.008899822,"domain_scores_codex":[0.999279,0.000148866,0.00003454364,0.000117308,0.0002926902,0.0001276645],"domain_scores_gemma":[0.9988532,0.0002839869,0.00007952583,0.0002970206,0.0004077783,0.00007842652],"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":[0.000199131,0.00009651818,0.001204106,0.0004082061,0.0001916572,0.0001187552,0.00008163153,0.07411283,0.001738128,0.01617489,0.8631957,0.04247843],"study_design_scores_gemma":[0.0002959216,0.0000440677,0.0009201097,0.000114511,0.0000917219,0.0001273411,0.00003270005,0.2680207,0.007141177,0.02363436,0.6994305,0.0001468895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005061779,0.000557227,0.2888727,0.001060723,0.001080512,0.0003145745,0.2873263,0.2759071,0.139819],"genre_scores_gemma":[0.07210658,0.0008424792,0.2620013,0.002140088,0.0005799512,0.001737208,0.3366496,0.2185339,0.1054089],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2066412,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01354291090407561,"score_gpt":0.2181131250259775,"score_spread":0.2045702141219018,"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."}}