{"id":"W6963608555","doi":"10.18739/a2736m29b","title":"Distributed Biological Observatory (DBO) and Conductivity-Temperature-Depth (CTD) data along DBO3 from Canada’s Three Oceans (C3O) project on board the CCGS (Canadian Coast Guard Ship) Sir Wilfrid Laurier, Southern Chukchi Sea, 2014","year":2014,"lang":"en","type":"dataset","venue":"California Digital Library","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coast guard; Observatory; On board; Data archive; Guard (computer science)","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","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002899417,0.0008945813,0.0009175165,0.0001235731,0.000524121,0.001426256,0.002251158,0.0005977299,0.001173336],"category_scores_gemma":[0.0001819558,0.0005775341,0.0001434884,0.0002506861,0.0003740525,0.000924598,0.0005338645,0.00121264,0.000780008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002831008,"about_ca_system_score_gemma":0.002352237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9249581,"about_ca_topic_score_gemma":0.9949413,"domain_scores_codex":[0.9959989,0.0003208801,0.0006723181,0.001416386,0.000608944,0.0009826112],"domain_scores_gemma":[0.9962769,0.0006805038,0.0003358394,0.001859644,0.000030427,0.0008167436],"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":[0.00009980762,0.00002138237,0.2165737,0.0000587199,0.0001132431,0.0001612795,0.000006500504,0.000005820856,1.162782e-7,0.000001927332,0.7816524,0.001305092],"study_design_scores_gemma":[0.0003128424,0.0001559561,0.02160842,0.0001057151,0.00006021862,0.00003025008,0.0001814463,0.0003217412,0.000001271107,0.0001626739,0.9762583,0.0008011432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.08367503,0.0009691853,9.732628e-7,0.001016411,0.0005627002,0.0007209827,0.9121646,0.0001014945,0.000788639],"genre_scores_gemma":[0.1363945,0.0001210595,0.000005165522,0.002210255,0.0009537395,0.000007745837,0.8601975,0.00003319892,0.00007687717],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1949653,"threshold_uncertainty_score":0.999998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623320997303546,"score_gpt":0.1914854942645624,"score_spread":0.1652522842915269,"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."}}