{"id":"W6962356404","doi":"10.1594/pangaea.325336","title":"Water temperature XBT profiles from cruise 18RN95009 (DCQC)","year":2005,"lang":"en","type":"dataset","venue":"Figshare","topic":"Rice Cultivation and Yield Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathythermograph; Cruise; Work (physics); Sea surface temperature","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":[],"consensus_categories":[],"category_scores_codex":[0.0005927699,0.001739482,0.001143665,0.002566349,0.000646857,0.001172344,0.002562845,0.001302472,0.04012755],"category_scores_gemma":[0.002633527,0.0008304731,0.0009437968,0.008032226,0.0002614469,0.0008500958,0.00112889,0.001180139,0.04927963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002766723,"about_ca_system_score_gemma":0.004021445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4115343,"about_ca_topic_score_gemma":0.4958519,"domain_scores_codex":[0.9994967,0.00004116692,0.00004771804,0.0001420158,0.0001686693,0.000103735],"domain_scores_gemma":[0.9984675,0.0001415102,0.0001826103,0.0002735648,0.000766873,0.0001678906],"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":[0.00004610965,0.00001059345,0.001485343,0.0002459145,0.00002622808,0.00001241665,0.0000195238,0.0004521956,0.00007981658,0.0001475899,0.9962024,0.001272028],"study_design_scores_gemma":[0.0003052412,0.0000140642,0.0296083,0.0002032513,0.00003677948,0.00002525809,0.0001051663,0.0008656217,0.0004675619,0.0003952704,0.9679317,0.00004194156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001048461,0.00001117595,0.0000161217,0.00001482771,0.000004624455,0.00000315986,0.9994472,0.00008940651,0.0003087145],"genre_scores_gemma":[0.0003402711,0.00001522323,0.00009322503,0.000007645906,0.000001816057,0.00001974688,0.9989616,0.00003505748,0.0005254243],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4115343,"threshold_uncertainty_score":0.8182778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03308269415566487,"score_gpt":0.2293360103509792,"score_spread":0.1962533161953143,"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."}}