{"id":"W6932252400","doi":"10.5683/sp2/39qgef","title":"Replication Data for: Washburn and Gillis, Saint John Harbour, New Brunswick (1993) (CC BY 4.0)","year":2020,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biota; Sediment; Tributary; Effluent; Water pollution; Harbour; Sampling (signal processing); Hydrography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00328357,0.002143127,0.001514629,0.00458076,0.002020775,0.002556245,0.003123698,0.0009773746,0.7957436],"category_scores_gemma":[0.01691049,0.001216378,0.0007808644,0.01320205,0.0007932633,0.001230363,0.002276147,0.001388292,0.5258278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003585355,"about_ca_system_score_gemma":0.01421777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2130734,"about_ca_topic_score_gemma":0.3074102,"domain_scores_codex":[0.9976575,0.0002413181,0.0002991241,0.0005477979,0.0008095063,0.000444701],"domain_scores_gemma":[0.9867735,0.001284651,0.0006699744,0.004500884,0.005803713,0.0009672801],"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":[0.0001800543,0.00003792513,0.001512986,0.0003125361,0.00002304746,0.00006380818,0.0001460158,0.0001299605,0.0003390875,0.0006425625,0.9638067,0.03280535],"study_design_scores_gemma":[0.0002073563,0.00003877269,0.03561341,0.000366301,0.00002398519,0.00004071008,0.0002292353,0.0001673517,0.0003930278,0.0004247152,0.9624492,0.00004596207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002201656,0.0001968587,0.001601694,0.0009737109,0.001683938,0.001038157,0.8594572,0.001904616,0.1309421],"genre_scores_gemma":[0.01105917,0.000487212,0.004181959,0.0003788802,0.0002333149,0.004005876,0.4905085,0.002404877,0.4867403],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7957436,"threshold_uncertainty_score":0.4236664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04884961469215187,"score_gpt":0.3073027883829079,"score_spread":0.258453173690756,"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."}}