{"id":"W6918194188","doi":"10.5885/45111sl-b5d073186f274136","title":"Environmental data from the Blanc-Sablon station, Quebec, Canada","year":2013,"lang":"en","type":"dataset","venue":"Nordicana D","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Environmental data; Data collection; Work (physics); Government (linguistics)","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":[0.0002604168,0.0005872097,0.0005023018,0.00005921389,0.0002877132,0.0001832191,0.004402933,0.0002491535,0.03063521],"category_scores_gemma":[0.0002125028,0.0004516962,0.0000484568,0.0001684339,0.0003067365,0.0002918084,0.001182221,0.000831857,0.01835766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001568581,"about_ca_system_score_gemma":0.002857521,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9998043,"about_ca_topic_score_gemma":0.9999627,"domain_scores_codex":[0.9958446,0.0003359551,0.000542526,0.001090171,0.0015553,0.0006314468],"domain_scores_gemma":[0.99281,0.0004857367,0.0005544685,0.005814252,0.00002245385,0.0003131273],"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":[0.00001206849,0.00004679133,0.0003888168,0.000009203123,0.0002682084,0.00005011724,0.00001161568,0.000005608435,0.00001400902,3.766805e-7,0.9987332,0.0004599422],"study_design_scores_gemma":[0.0003235791,0.000006865753,0.0189496,0.0000336711,0.0003064552,0.000002404161,0.0001593935,0.00005073187,0.00000358379,0.000009759449,0.9796382,0.0005157794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001459579,0.0007673895,0.000001967363,0.0008420612,0.0006689907,0.0006102826,0.995565,0.00003546001,0.00004926606],"genre_scores_gemma":[0.0003993595,0.0001817855,0.00002950056,0.002093388,0.0009023638,0.00006116279,0.9954283,0.0001276054,0.0007765353],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01909507,"threshold_uncertainty_score":0.9997935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229586574821325,"score_gpt":0.2324318746991042,"score_spread":0.210136008950891,"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."}}