{"id":"W7036541114","doi":"","title":"CHAR Technologies Announces $2.5M from the Government of Québec for Saint-Félicien Biocarbon and Green Hydrogen Project","year":2024,"lang":"en","type":"other","venue":"","topic":"Sesquiterpenes and Asteraceae Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Char; Scope (computer science); Hydrogen","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":[],"consensus_categories":[],"category_scores_codex":[0.00006307096,0.0002137335,0.0002252827,0.00002230267,0.00002687811,0.00001627787,0.0002269267,0.0001796983,0.00001167145],"category_scores_gemma":[0.00002669265,0.00012064,0.00008850571,0.00004443013,0.000176862,8.28376e-7,0.0003676214,0.00004720079,0.000001957477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001475836,"about_ca_system_score_gemma":0.00004479214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01498009,"about_ca_topic_score_gemma":0.008575591,"domain_scores_codex":[0.999182,0.00001092304,0.0001423767,0.0003775529,0.0001415481,0.0001455662],"domain_scores_gemma":[0.9995404,0.00001809719,0.0001065919,0.0003106794,0.00001500382,0.000009185501],"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":[0.0001591014,0.00009893499,0.004134364,0.0005963839,0.00250636,0.000003763113,0.0006780607,4.094852e-7,0.1435934,0.0004715679,0.7723835,0.07537422],"study_design_scores_gemma":[0.0001587597,0.0002121456,0.00002958744,0.0001238714,0.00009433712,0.000001261692,0.001536712,0.000008931187,0.02678584,0.00008481823,0.9707859,0.0001778316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"other","genre_scores_codex":[0.1962747,0.4718243,0.0002427245,0.01007408,0.0009005345,0.005510963,0.008771657,0.0004679553,0.305933],"genre_scores_gemma":[0.1468242,0.01078723,0.001049624,0.0005379501,0.00110619,0.0004857123,0.0002493726,0.0004791782,0.8384806],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5325475,"threshold_uncertainty_score":0.9915792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0104562349069417,"score_gpt":0.2454501143802411,"score_spread":0.2349938794732994,"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."}}