{"id":"W4385338922","doi":"10.52202/069564-0237","title":"AIDRES: A Database for the Decarbonisation of the Heavy Industry in Europe","year":2023,"lang":"en","type":"article","venue":"","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Yara International; Vrije Universiteit Brussel; European Commission; European Chemical Industry Council","keywords":"Computer science; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001310366,0.001988178,0.001519857,0.008734548,0.0002578957,0.002848216,0.001887402,0.001527605,0.01807549],"category_scores_gemma":[0.004365886,0.000611827,0.001338521,0.01475813,0.0001896496,0.002287506,0.001512035,0.0008648385,0.0119991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009234054,"about_ca_system_score_gemma":0.001550881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008341286,"about_ca_topic_score_gemma":0.00466761,"domain_scores_codex":[0.9986884,0.0001897251,0.0004373425,0.0002262227,0.0003718251,0.00008640849],"domain_scores_gemma":[0.997523,0.0007129042,0.0005871546,0.0004336026,0.0005830851,0.0001602745],"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":[0.00105673,0.0002619957,0.02516483,0.01343293,0.001012785,0.0009283767,0.0004333388,0.08095223,0.00539174,0.03564152,0.6003969,0.2353266],"study_design_scores_gemma":[0.0001131061,0.00005648234,0.01116753,0.0006244032,0.0001399134,0.0002241759,0.0001117451,0.005983769,0.001691467,0.005244155,0.9745668,0.00007645479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005982806,0.002035664,0.009980081,0.0001321569,0.00007784886,0.0001132436,0.9666282,0.00367265,0.01137733],"genre_scores_gemma":[0.01453747,0.002243555,0.01380274,0.0001118219,0.00002900018,0.000268104,0.9661391,0.0005619826,0.002306169],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01807549,"threshold_uncertainty_score":0.06046855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098082746785395,"score_gpt":0.3816374544612192,"score_spread":0.2718291797826797,"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."}}