{"id":"W1713084328","doi":"10.1023/a:1006716406751","title":"Estimating biomass of white spruce seedlings with vertical photo imagery","year":2000,"lang":"en","type":"article","venue":"New Forests","topic":"Forest ecology and management","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Forest Research Institute","funders":"","keywords":"Understory; Biomass (ecology); Basal area; Seedling; Silhouette; Tree allometry; Productivity; Horticulture; Silviculture; Stem-and-leaf display; Canopy; Botany; Biology; Environmental science; Forestry; Agronomy; Ecology; Biomass partitioning; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010207,0.0001053495,0.0001227641,0.00002245024,0.00009699626,0.000008897242,0.0001643702,0.00004859017,0.00775437],"category_scores_gemma":[0.00001555921,0.00008523034,0.00003186271,0.0001679231,0.0002166699,0.0001610477,0.0001071828,0.00006908146,0.0006255094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004059377,"about_ca_system_score_gemma":0.00001191295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004614623,"about_ca_topic_score_gemma":0.001045189,"domain_scores_codex":[0.9991667,0.00001347774,0.000158384,0.0002204122,0.0001853523,0.0002556862],"domain_scores_gemma":[0.9996402,0.00002326452,0.00003097602,0.0002020713,0.000003237549,0.0001002778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002927399,0.0002165292,0.936385,0.00004893737,0.00004734303,0.0001057053,0.0009564562,0.02255694,0.002746442,0.000818592,0.02092057,0.01490471],"study_design_scores_gemma":[0.0006988607,0.000249726,0.9772781,0.00003399695,0.00003284049,0.00001797757,0.00001219576,0.01156302,0.002990069,0.00302113,0.003916134,0.0001859889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705477,0.000006670739,0.002372601,0.000224852,0.00005359176,0.0001542526,8.731745e-7,0.00003891492,0.02660055],"genre_scores_gemma":[0.9835057,0.000001023946,0.0135209,0.0001981536,0.0000262224,0.000007724346,0.000002874568,0.00001143014,0.002725968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04089302,"threshold_uncertainty_score":0.9931527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00535496589836053,"score_gpt":0.211285098277894,"score_spread":0.2059301323795334,"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."}}