{"id":"W6967173733","doi":"10.5061/dryad.fh505/2","title":"Vemco temperature-depth recorder data. A Canadian Healthy Oceans Network Population Connectivity project, PC-06","year":2014,"lang":"en","type":"other","venue":"DRYAD","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Population; Climate change; Context (archaeology); Identification (biology)","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":[0.000749258,0.0009683814,0.0005102772,0.003088564,0.001576036,0.00148435,0.002653824,0.0005065408,0.1016348],"category_scores_gemma":[0.003477758,0.0006120419,0.0006509639,0.006419252,0.0003066363,0.0006866509,0.001175206,0.0008951848,0.03089206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009308434,"about_ca_system_score_gemma":0.02851799,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9888358,"about_ca_topic_score_gemma":0.9924218,"domain_scores_codex":[0.9992744,0.00002845721,0.00003231508,0.00008270239,0.0004066013,0.0001755128],"domain_scores_gemma":[0.9979895,0.00005156558,0.00006539546,0.0001309311,0.001573606,0.0001889646],"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":[0.00005436813,0.00001413496,0.003788622,0.0001159002,0.00001438506,0.00002024315,0.00005501493,0.0003028108,0.0001214506,0.0008698022,0.9807624,0.01388077],"study_design_scores_gemma":[0.00009636125,0.00001063972,0.05287542,0.0001857791,0.00003304373,0.00002694007,0.0002685477,0.001341431,0.0006410185,0.0005467713,0.9439281,0.00004584737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0009823907,0.000100055,0.0005172537,0.0002729766,0.00006952163,0.0000951113,0.9636378,0.0005188804,0.03380602],"genre_scores_gemma":[0.0117036,0.0004049567,0.004010884,0.0002120649,0.00003760062,0.0002717079,0.8908258,0.0008353211,0.09169803],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1016348,"threshold_uncertainty_score":0.3400022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03379422722601797,"score_gpt":0.3017606774028173,"score_spread":0.2679664501767993,"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."}}