{"id":"W7099649111","doi":"","title":"EXTERNAL FINANCING OF R&D INTENSIVE SME EXPORTERS ACROSS CANADIAN","year":2013,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Access to finance; Competitive advantage; External financing; Empirical evidence; Comparative advantage; Production (economics)","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":[0.0007493419,0.0001783893,0.000257362,0.002037377,0.001741579,0.002308985,0.0005513894,0.0002878173,0.007055516],"category_scores_gemma":[0.003936116,0.0001999528,0.0002466704,0.003421301,0.0008450228,0.0005828845,0.001541719,0.00055869,0.0002900834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01720697,"about_ca_system_score_gemma":0.02128497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9111216,"about_ca_topic_score_gemma":0.9607474,"domain_scores_codex":[0.999275,0.00004169794,0.00003814999,0.000104679,0.0002086883,0.0003318101],"domain_scores_gemma":[0.9925686,0.0007468404,0.002709231,0.0002218174,0.001844461,0.001909086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001783015,0.00004817234,0.9638078,0.0001109825,0.0000535682,0.0007004742,0.002878969,0.0007814458,0.001831896,0.005032608,0.002408713,0.02216726],"study_design_scores_gemma":[0.000007476624,0.0000222107,0.9869941,0.00004967491,0.00002455196,0.0001494321,0.002873819,0.0003488442,0.0005077343,0.0001379161,0.008870776,0.00001337404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881386,0.0004093576,0.0001584024,0.0006924839,0.000003372766,0.00001759802,0.001351892,0.00001448409,0.009213797],"genre_scores_gemma":[0.9927149,0.0005392936,0.00009154461,0.00007798531,0.00000474078,0.000006289421,0.0006503664,0.000005228473,0.00590966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08887839,"threshold_uncertainty_score":0.1788036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02537661814773934,"score_gpt":0.2434399193423131,"score_spread":0.2180633011945738,"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."}}