{"id":"W7036645295","doi":"","title":"Canada formalizes 30% federal ITC credit, other incentives","year":2023,"lang":"en","type":"other","venue":"","topic":"Mediterranean and Iberian flora and fauna","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Incentive; Government (linguistics); Control (management); Work (physics); Context (archaeology); Action (physics)","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":[],"consensus_categories":[],"category_scores_codex":[0.002189954,0.0006570936,0.0006234418,0.002906518,0.004411332,0.004882247,0.002131037,0.003891202,0.1398024],"category_scores_gemma":[0.009099124,0.0006719377,0.000821661,0.003275977,0.001032267,0.0008385325,0.002137795,0.003028674,0.0283953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02616958,"about_ca_system_score_gemma":0.1332973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9588473,"about_ca_topic_score_gemma":0.9721144,"domain_scores_codex":[0.9960365,0.0001699205,0.00008910965,0.0002032362,0.001696769,0.00180458],"domain_scores_gemma":[0.988528,0.0006558661,0.0002964632,0.0005035711,0.007595453,0.002420649],"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":[0.0001191981,0.0001332828,0.003729902,0.00006845067,0.00002104107,0.00007952018,0.0001104339,0.0004345136,0.0002954821,0.02418097,0.9392601,0.03156723],"study_design_scores_gemma":[0.000109584,0.00002447715,0.01135844,0.00006752861,0.00002159608,0.00005055991,0.0001313291,0.0009574626,0.0004531826,0.001064495,0.9857362,0.00002514971],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01144276,0.0006357537,0.001435112,0.0116502,0.0009495351,0.0006767318,0.03061685,0.001720785,0.9408723],"genre_scores_gemma":[0.03906156,0.0004107847,0.001191825,0.005145967,0.000164025,0.0002306661,0.007517051,0.0002820984,0.9459961],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1398024,"threshold_uncertainty_score":0.4676858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02050176553860025,"score_gpt":0.2060203073539819,"score_spread":0.1855185418153817,"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."}}