{"id":"W6967127486","doi":"10.5065/d6vd6whk","title":"SWL13 Bottle data. Version 2.0","year":2015,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Coast guard; Cruise; Hydrography; Water bottle; Longitude; Latitude; Bottle; Raw data","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002573084,0.0008797157,0.0009070158,0.0004133651,0.0002757427,0.000301225,0.004699708,0.0008956912,0.003002931],"category_scores_gemma":[0.001963267,0.0009459231,0.00008683858,0.001509394,0.0001875724,0.001189303,0.003609168,0.001546824,0.1322561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002660746,"about_ca_system_score_gemma":0.002484508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007138461,"about_ca_topic_score_gemma":0.001967157,"domain_scores_codex":[0.9942449,0.000664126,0.0006850748,0.001646613,0.001791274,0.0009679865],"domain_scores_gemma":[0.988928,0.0001833003,0.0006885055,0.008557755,0.000980604,0.0006618605],"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":[0.00005076666,0.0001233905,0.0001003361,0.000241275,0.0001113277,0.0002033142,0.0000193844,0.00001954557,0.0002175584,0.000001498923,0.9988676,0.00004397982],"study_design_scores_gemma":[0.0007553143,0.00006962494,0.0004686874,0.0003203032,0.0002395633,0.00000442279,0.00005284682,0.00006119911,0.00005688676,0.000009411729,0.9969603,0.001001417],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006217222,0.004279444,6.972611e-7,0.00006067499,0.003162259,0.000412904,0.9907091,0.0005310447,0.0002222131],"genre_scores_gemma":[0.000009797213,0.0001685345,0.0006869909,0.0006223316,0.001524902,0.00001698858,0.9962634,0.0002694164,0.0004376211],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1292532,"threshold_uncertainty_score":0.9992991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06926219499026162,"score_gpt":0.2992989499596709,"score_spread":0.2300367549694093,"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."}}