{"id":"W6918204405","doi":"10.5885/45318sl-f1c26eb4d6c54f3a","title":"Climate station data from Macpès research forest in the Rimouski area, Quebec, Canada","year":2018,"lang":"en","type":"dataset","venue":"Nordicana D","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Vegetation (pathology); Forest cover; Effects of global warming","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","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004792618,0.0005524816,0.0006255408,0.0006157969,0.0004729929,0.0003978336,0.007438791,0.0003993633,0.0025393],"category_scores_gemma":[0.001840001,0.0004401866,0.00004578954,0.001443865,0.0006072706,0.0003442557,0.001819741,0.002205561,0.003296337],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002188953,"about_ca_system_score_gemma":0.007282447,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9998012,"about_ca_topic_score_gemma":0.9999989,"domain_scores_codex":[0.9905891,0.001859537,0.0007993941,0.001511955,0.003661813,0.001578193],"domain_scores_gemma":[0.9898717,0.001801057,0.0004427078,0.007240263,0.0003588449,0.0002854736],"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":[0.0001206297,0.00009047696,0.001589014,0.00006113518,0.00006614594,0.0003654614,0.00004960528,0.000006184876,0.000002439543,0.000008541383,0.9974768,0.0001635432],"study_design_scores_gemma":[0.000486962,0.00003313004,0.02500778,0.0002045371,0.00009876055,0.000003500779,0.0004357757,0.0002074836,0.000001265692,0.000122361,0.9729525,0.0004459795],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004593722,0.0002318285,8.642974e-7,0.0007536731,0.0004363916,0.00104168,0.9924778,0.00003189689,0.0004321378],"genre_scores_gemma":[0.002290252,0.0002139351,0.00003806772,0.0005415872,0.0008635148,0.0001472769,0.995679,0.0001341965,0.00009223288],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02452436,"threshold_uncertainty_score":0.999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1398232804090344,"score_gpt":0.3821973501050366,"score_spread":0.2423740696960021,"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."}}