{"id":"W2132071515","doi":"10.5558/tfc82562-4","title":"Predicting lodgepole pine site index from climatic parameters in Alberta","year":2006,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest ecology and management","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas","funders":"Pacific Northwest Research Station; U.S. Forest Service; Forest Resource Improvement Association of Alberta; U.S. Department of Agriculture","keywords":"Site index; Pinus contorta; Environmental science; Longitude; Latitude; Physical geography; Productivity; Forestry; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004675493,0.0004140619,0.0002215674,0.0007461321,0.0004102226,0.000822033,0.0005004539,0.0002153018,0.0007632487],"category_scores_gemma":[0.0007446929,0.000205206,0.0003220215,0.0008145176,0.0002201603,0.0001605281,0.0003084101,0.0002121221,0.0001865028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004455992,"about_ca_system_score_gemma":0.003617778,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8976325,"about_ca_topic_score_gemma":0.9436785,"domain_scores_codex":[0.9998627,0.0000191422,0.000004969124,0.00003473955,0.00004203571,0.00003638293],"domain_scores_gemma":[0.9996997,0.00007910484,0.00003302827,0.00001331676,0.0001124124,0.00006251636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001245912,0.00004802784,0.9446738,0.00002077596,0.00007035332,0.0001136509,0.00007715269,0.04339125,0.00178315,0.0001158993,0.0007861856,0.008795244],"study_design_scores_gemma":[0.00002041795,0.00002017644,0.9055596,0.00001356133,0.00003781238,0.00003744921,0.0001863159,0.09275845,0.0003391914,0.0001013949,0.0009127024,0.00001292658],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975162,0.0001702148,0.0005978704,0.00003400934,0.000004149259,0.000007443594,0.0008181132,0.00004781221,0.0008042433],"genre_scores_gemma":[0.9967919,0.0001435743,0.0007580618,0.00001243969,0.000002205165,0.00000449643,0.001664932,0.00000893281,0.0006134041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1023675,"threshold_uncertainty_score":0.2059407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005600303684609134,"score_gpt":0.2005461589357574,"score_spread":0.1949458552511482,"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."}}