{"id":"W6964816240","doi":"10.25976/gzy7-sl16","title":"RivTemp--Indian Bay Ecosystem Corporation","year":2021,"lang":"en","type":"dataset","venue":"DataStream","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bay; General partnership; Corporation; Watershed; Foundation (evidence); Variety (cybernetics)","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001834328,0.0003038351,0.0002631595,0.00008182212,0.0001254075,0.0001731623,0.0007209389,0.0001871494,0.03487108],"category_scores_gemma":[0.00003234216,0.0002926638,0.00007282764,0.000298335,0.00006523343,0.0003116481,0.0007779369,0.0002308987,0.05380403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001523081,"about_ca_system_score_gemma":0.00002579809,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003027907,"about_ca_topic_score_gemma":0.02005443,"domain_scores_codex":[0.9983202,0.00008520556,0.000298691,0.0005571854,0.0004004505,0.0003382633],"domain_scores_gemma":[0.998279,0.00002419532,0.0002393611,0.001310043,0.000004745136,0.0001426439],"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":[0.000003089389,0.00006193924,0.0003117035,0.0000699194,0.00002303613,0.000119558,0.00000843485,0.00003392244,0.000001669863,0.000007534366,0.9985922,0.0007670114],"study_design_scores_gemma":[0.000135329,0.00003207698,0.0002139241,0.00004660156,0.0000554853,0.00001309119,0.000007680964,0.00002848424,0.000006629019,0.00001016047,0.9991608,0.0002897657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002902642,0.00001699901,0.000002212736,0.0000793175,0.0005174452,0.0002603052,0.9960697,0.00003241449,0.002731347],"genre_scores_gemma":[0.0001494124,0.00009313688,0.00008377285,0.0002378978,0.0003169367,0.00003167933,0.9967057,0.00001772589,0.002363815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01893295,"threshold_uncertainty_score":0.9999526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057527610713256,"score_gpt":0.2292748632876514,"score_spread":0.2186995871805188,"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."}}