{"id":"W1971430271","doi":"10.1007/s10086-008-1013-1","title":"Identification of selected internal wood characteristics in computed tomography images of black spruce: a comparison study","year":2009,"lang":"en","type":"article","venue":"Journal of Wood Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"FPInnovations; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; FPInnovations; New Brunswick Innovation Foundation; Ministry of Natural Resources","keywords":"Black spruce; Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Artificial neural network; Mathematics; Computed tomography; Computer science; Geography; Forestry; Taiga","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001395205,0.0001239366,0.000466696,0.000649642,0.00005525753,0.00008355962,0.0009745061,0.00004799558,0.00002467914],"category_scores_gemma":[0.0003511368,0.0001041639,0.00009386492,0.001963484,0.000352118,0.0003705949,0.00007432501,0.0004596944,0.000001294381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005921279,"about_ca_system_score_gemma":0.0002744205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001324573,"about_ca_topic_score_gemma":0.000004573739,"domain_scores_codex":[0.9970355,0.00005979028,0.001296927,0.0002025566,0.001130187,0.0002750587],"domain_scores_gemma":[0.9971871,0.00007794717,0.001212845,0.0002419663,0.00115741,0.0001227661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001033333,0.001675884,0.08438206,0.00004714735,0.00002506271,0.00001899749,0.001337983,0.00004159183,0.9105895,0.000009197387,0.00006703469,0.001702216],"study_design_scores_gemma":[0.0008087522,0.000521729,0.3677187,0.000220002,0.00001920366,0.00002003089,0.001149782,0.001243807,0.628168,0.00004084212,0.000004205418,0.00008495027],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991945,0.00007435553,0.0001755005,0.0001239513,0.00007937828,0.00008424938,0.000009040969,0.000006844601,0.0002521482],"genre_scores_gemma":[0.999626,0.00001450253,0.0002469823,0.00000511878,0.0000722467,4.626441e-7,9.685331e-7,0.000005137962,0.00002852823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2833367,"threshold_uncertainty_score":0.4247679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0168489330766186,"score_gpt":0.3177706430237948,"score_spread":0.3009217099471762,"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."}}