{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001563011,0.0009032058,0.0005496743,0.001425382,0.003298818,0.003569151,0.001279767,0.002823916,0.4621397],"category_scores_gemma":[0.001653221,0.0004983392,0.0006582051,0.0009836429,0.0009939626,0.0009955681,0.001232017,0.002164749,0.1413232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01389274,"about_ca_system_score_gemma":0.02287146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7502772,"about_ca_topic_score_gemma":0.8935187,"domain_scores_codex":[0.9987999,0.00004800463,0.0000126987,0.00008889593,0.0007685701,0.0002818011],"domain_scores_gemma":[0.9969946,0.0001193613,0.00003922581,0.0001204712,0.001685613,0.001040632],"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":[0.00009075171,0.00005231076,0.0002276901,0.0000273352,0.000003509988,0.00003665648,0.00001214793,0.00008213862,0.0006442561,0.002121339,0.9810721,0.01562973],"study_design_scores_gemma":[0.00002837942,0.00003053705,0.001275943,0.00001659761,0.000002026155,0.00001417968,0.00004122661,0.0001938756,0.0003762761,0.0002692056,0.9977418,0.000009847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003269717,0.001837248,0.002129679,0.02124175,0.004400028,0.0004474244,0.02746597,0.003349706,0.9358585],"genre_scores_gemma":[0.003570952,0.0002441523,0.0005668935,0.001414982,0.00008249188,0.00003013558,0.003093283,0.0002728367,0.9907244],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4621397,"threshold_uncertainty_score":0.7671924,"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."}}