{"id":"W4398801008","doi":"10.7910/dvn/u2hvb6/kltb9m","title":"A__1__20170510_132756.wav","year":2019,"lang":"hi","type":"dataset","venue":"Harvard Dataverse","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Liana; Replication (statistics); Abundance (ecology); Tropical and subtropical dry broadleaf forests; Geography; Biology; Ecology; Forestry; Virology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001268348,0.002566586,0.00206926,0.007163545,0.0009646611,0.004668729,0.003544261,0.002100632,0.4186442],"category_scores_gemma":[0.01015652,0.001115802,0.001121809,0.01456536,0.0005602171,0.00297673,0.003561289,0.001585059,0.4346601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159027,"about_ca_system_score_gemma":0.002723313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02442373,"about_ca_topic_score_gemma":0.0340657,"domain_scores_codex":[0.9989066,0.0001847944,0.0001312005,0.0003441228,0.0002271566,0.0002060127],"domain_scores_gemma":[0.9961776,0.001161447,0.0004386762,0.0008837156,0.0007990488,0.0005394592],"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":[0.00003143559,0.000004837203,0.0002630913,0.000485804,0.00001879509,0.000005146138,0.00001274745,0.0000619025,0.00003998831,0.0003900436,0.9972907,0.001395478],"study_design_scores_gemma":[0.0001130336,0.000007384705,0.001339754,0.0003209944,0.00002233529,0.00001236109,0.00003409059,0.00008337144,0.0001473882,0.001221521,0.9966758,0.00002185188],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001505342,0.00003896784,0.0000278442,0.00003440228,0.0000108184,0.000003064482,0.998582,0.0003566679,0.0009311709],"genre_scores_gemma":[0.0002400999,0.00008705333,0.0001399475,0.00007382803,0.00001113602,0.00005447882,0.9976748,0.0003623134,0.00135642],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4186442,"threshold_uncertainty_score":0.8292335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02719519024070898,"score_gpt":0.2494126468945315,"score_spread":0.2222174566538225,"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."}}